Archive 4 checkpoints (1-4)

paper-releases/pbisc-diffusion/updates/20261012T131501Z-strictpairs-final-caption/diffusion/dataset/server_1/model8/plans/paper_figures_strictpairs_20261012/archive/20261012T131501Z-strictpairs-final-caption/assemble_manuscript.py

@@ -0,0 +1,592 @@
+#!/usr/bin/env python3
+"""Stage the PBISC-Diffusion Figure 1--5 manuscript without changing its Git tree.
+
+--preview emits an explicitly incomplete review draft. --require-complete refuses
+until every strict unit and its source binding has been verified, then uses the
+same staged file map. No Git, archive or network write is performed here.
+"""
+from __future__ import annotations
+
+import argparse
+import csv
+import hashlib
+import json
+import re
+import shutil
+import subprocess
+from collections import defaultdict
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parents[1]
+CANON = Path('/home/sj_server_1/PBISC/paper-release-20260928/manuscript')
+STAGE = ROOT / 'manuscript'
+EDITS = STAGE / 'edits'
+COHORTS = ('ye2026_sepsis', 'imperial_eskd', 'giroux2022', 'ji2025_chili')
+FIGURES = {
+    'fig1_overview.pdf': 'fig1_overview.pdf',
+    'fig2_ablation_and_support.pdf': 'fig2_ablation_and_support.pdf',
+    'fig4_historical_5fold_separate.pdf': 'fig4_historical_5fold_separate.pdf',
+}
+FINAL_FIGURES = {
+    'fig3_healthy_strict_oof.pdf': 'fig3_healthy_strict_oof.pdf',
+    'fig3_realism_metrics.pdf': 'fig3_realism_metrics.pdf',
+    'fig3_canonical_marker_dotplot.pdf': 'fig3_canonical_marker_dotplot.pdf',
+    'fig3_umap_by_celltype.pdf': 'fig3_umap_by_celltype.pdf',
+    'fig3_composition_fractions.pdf': 'fig3_composition_fractions.pdf',
+    'fig3_runtime_components.pdf': 'fig3_runtime_components.pdf',
+    'fig4_disease_strict_draws.pdf': 'fig4_disease_strict_draws.pdf',
+    'fig4_disease_signal_strict.pdf': 'fig4_disease_signal_strict.pdf',
+    'fig4_disease_signal_scatter.pdf': 'fig4_disease_signal_scatter.pdf',
+    'fig4_disease_signal_heatmap.pdf': 'fig4_disease_signal_heatmap.pdf',
+    'fig4_disease_signal_cat.pdf': 'fig4_disease_signal_cat.pdf',
+    'fig4_deconvolution_strict.pdf': 'fig4_deconvolution_strict.pdf',
+    'fig4_deconvolution_expression_strict.pdf': 'fig4_deconvolution_expression_strict.pdf',
+    'fig5_rare_states_strict.pdf': 'fig5_rare_states_strict.pdf',
+    'fig5_rare_visuals_strict.pdf': 'fig5_rare_visuals_strict.pdf',
+    'fig5_all_states_strict.pdf': 'fig5_all_states_strict.pdf',
+    'fig5_behcet_rules_strict.pdf': 'fig5_behcet_rules_strict.pdf',
+}
+
+
+def digest(path: Path) -> str:
+    h = hashlib.sha256()
+    with path.open('rb') as f:
+        for chunk in iter(lambda: f.read(1024 * 1024), b''):
+            h.update(chunk)
+    return h.hexdigest()
+
+
+def document(path: Path) -> dict:
+    return json.loads(path.read_text())
+
+
+def rows(path: Path) -> list[dict[str, str]]:
+    with path.open(newline='') as f:
+        return list(csv.DictReader(f))
+
+
+def tracked_sources() -> list[Path]:
+    raw = subprocess.check_output(['git', '-C', str(CANON), 'ls-files', '-z'])
+    paths = [Path(p.decode()) for p in raw.split(b'\0') if p]
+    wanted = {'.tex', '.bib', '.cls', '.bst'}
+    return [p for p in paths if p.suffix in wanted or
+            (p.parts[0] == 'figures' and p.suffix.lower() in {'.pdf', '.png'})]
+
+
+def checked_provenance(path: Path, label: str) -> dict:
+    if not path.is_file():
+        raise ValueError(f'{label}: missing {path}')
+    item = document(path)
+    for entry in item.get('sources', []) + item.get('outputs', []):
+        source = Path(entry['path'])
+        if not source.is_file() or digest(source) != entry['sha256']:
+            raise ValueError(f'{label}: source/output hash mismatch: {source}')
+    return item
+
+
+def strict_gate() -> tuple[list[str], dict]:
+    gaps = []
+    readiness_path = ROOT / 'reports/figures234_readiness.json'
+    readiness = document(readiness_path) if readiness_path.is_file() else {}
+    if readiness.get('schema') != 'pbisc.paper.figures234.v1' or readiness.get('status') != 'complete':
+        gaps.append('Figures 2--4 readiness is not complete')
+    f2, f3, f4 = (readiness.get(k, {}) for k in ('figure2', 'figure3', 'figure4'))
+    if f2.get('strict_complete_units') != 20 or f2.get('strict_missing') or not f2.get('pretrain_composition_ready'):
+        gaps.append('Figure 2 needs 20/20 strict healthy support units')
+    if (f3.get('strict_complete_folds') != 5 or not f3.get('visual_export_ready') or
+            not f3.get('extras_complete') or not f3.get('runtime_ready')):
+        gaps.append('Figure 3 needs 5/5 folds, visual, extras and time receipts')
+    if (set(f4.get('strict_complete_draws', {})) != set(COHORTS) or
+            any(f4['strict_complete_draws'].get(c) != 5 for c in COHORTS) or
+            any(f4.get(k) for k in ('contrast_missing', 'deconvolution_missing',
+                                    'deconvolution_signal_missing'))):
+        gaps.append('Figure 4 needs 5/5 strict draws per cohort and contrast/deconvolution evidence')
+    expected_healthy = {(f'fold{fold}', n) for fold in range(5) for n in (5, 10, 20, 40)}
+    expected_disease = {(c, f'draw{draw}') for c in COHORTS for draw in range(5)}
+    curve = rows(ROOT / 'source_data/fig2_strict_curve.csv')
+    if {(r['fold'], int(r['n_pairs'])) for r in curve} != expected_healthy:
+        gaps.append('Figure 2 strict CSV has incomplete fold/size units')
+    healthy = rows(ROOT / 'source_data/fig3_per_sample.csv')
+    if {r['fold'] for r in healthy} != {f'fold{n}' for n in range(5)}:
+        gaps.append('Figure 3 strict per-sample CSV has incomplete folds')
+    disease = rows(ROOT / 'source_data/fig4_strict_per_sample.csv')
+    if {(r['cohort'], r['draw']) for r in disease} != expected_disease or any(
+            r.get('design') != 'strict_exact5_donor_draw' for r in disease):
+        gaps.append('Figure 4 strict CSV has incomplete or mixed-design draws')
+    for filename, table in [('fig2_strict_curve.csv', curve), ('fig3_per_sample.csv', healthy),
+                            ('fig4_strict_per_sample.csv', disease)]:
+        if not table or any(not r.get('support_sha256') for r in table):
+            gaps.append(f'{filename} lacks source-bound support hashes')
+    for record in curve + healthy + disease:
+        source = record.get('summary')
+        source_hash = record.get('summary_sha256')
+        if source and source_hash and (not Path(source).is_file() or digest(Path(source)) != source_hash):
+            gaps.append(f'score summary hash mismatch: {source}')
+            break
+    for table, kind in ((curve, 'healthy'), (healthy, 'healthy'), (disease, 'disease')):
+        for record in table:
+            cohort = record.get('cohort', 'immicro')
+            unit = record.get('fold') if kind == 'healthy' else record.get('draw')
+            suffix = f'{unit}/n{record["n_pairs"]}' if table is curve else (
+                f'{unit}/n5' if kind == 'healthy' else unit)
+            support = ROOT / 'protocol/splits' / cohort / kind / suffix / 'support.json'
+            if not support.is_file() or document(support).get('sha256') != record.get('support_sha256'):
+                gaps.append(f'{cohort}/{kind}/{suffix}: source support mismatch')
+                break
+            summary = ROOT / 'scores' / cohort / kind / suffix / 'score/summary.json'
+            score_sha = record.get('score_sha256') or record.get('summary_sha256')
+            if not summary.is_file() or digest(summary) != score_sha:
+                gaps.append(f'{cohort}/{kind}/{suffix}: score summary hash mismatch')
+                break
+    rare_path = ROOT / 'reports/rare_provenance.json'
+    rare = document(rare_path) if rare_path.is_file() else {}
+    units = rare.get('units', [])
+    if (rare.get('schema') != 'pbisc.figure5.analysis.v1' or len(units) != 20 or
+            {(u.get('cohort'), u.get('unit')) for u in units} != expected_disease or
+            any(u.get('design') != 'strict5pair' or u.get('evidence_tier') != 'strict'
+                or not u.get('support_sha256') for u in units)):
+        gaps.append('Figure 5 needs all 20 strict rare-state receipts')
+    rare_table = rows(ROOT / 'source_data/rare_summary.csv')
+    if (not rare_table or {r.get('evidence_tier') for r in rare_table} != {'strict'} or
+            {(r['cohort'], r['unit']) for r in rare_table} != expected_disease):
+        gaps.append('Figure 5 rare-state CSV is absent, diagnostic or incomplete')
+    for cohort, unit in expected_disease:
+        subset = [r for r in rare_table if r.get('cohort') == cohort and r.get('unit') == unit]
+        if {r.get('arm') for r in subset} != {'raw', 'refcal', 'pairedcal', 'scsemi', 'lora'}:
+            gaps.append(f'Figure 5 strict arms incomplete: {cohort}/{unit}')
+            break
+    for unit in units:
+        support = ROOT / 'protocol/splits' / str(unit.get('cohort')) / 'disease' / str(unit.get('unit')) / 'support.json'
+        if not support.is_file() or document(support).get('sha256') != unit.get('support_sha256'):
+            gaps.append(f'Figure 5 strict support hash mismatch: {unit.get("cohort")}/{unit.get("unit")}')
+            break
+    if readiness.get('status') == 'complete':
+        runtime = ROOT / 'source_data/fig3_runtime.csv'
+        runtime_meta = ROOT / 'source_data/fig3_runtime.json'
+        visual = ROOT / 'source_data/fig3_visual_data.npz'
+        visual_meta = ROOT / 'source_data/fig3_visual_data.json'
+        if (not runtime.is_file() or not runtime_meta.is_file() or
+                document(runtime_meta).get('csv_sha256') != digest(runtime)):
+            gaps.append('Figure 3 runtime source/receipt hash mismatch')
+        if (not visual.is_file() or not visual_meta.is_file() or
+                document(visual_meta).get('npz_sha256') != digest(visual)):
+            gaps.append('Figure 3 visual source/receipt hash mismatch')
+        extras = ROOT / 'source_data/fig3_extras.csv'
+        if not extras.is_file() or not rows(extras):
+            gaps.append('Figure 3 realism extras CSV is missing')
+        for name in ('fig4_strict_contrast.csv', 'fig4_deconvolution.csv',
+                     'fig4_deconvolution_signal.csv', 'fig4_corrected_statistics.csv',
+                     'fig4_cross_draw_donor_ci.csv', 'fig4_donor_aware_signal.csv',
+                     'fig4_donor_aware_summary.csv', 'fig4_donor_aware_genes.csv',
+                     'fig4_donor_aware_cat.csv'):
+            path = ROOT / 'source_data' / name
+            if not path.is_file() or not rows(path):
+                gaps.append(f'Figure 4 required source table missing: {name}')
+        cross = ROOT / 'source_data/fig4_cross_draw_donor_ci.csv'
+        cross_receipt = ROOT / 'source_data/fig4_cross_draw_donor_ci.json'
+        if (not cross_receipt.is_file() or not cross.is_file() or
+                document(cross_receipt).get('csv_sha256') != digest(cross) or
+                {r.get('cohort') for r in rows(cross)} != set(COHORTS)):
+            gaps.append('Figure 4 five-draw donor-cluster CI source or receipt mismatch')
+        corrected = ROOT / 'source_data/fig4_donor_aware_signal.csv'
+        corrected_provenance = ROOT / 'source_data/fig4_donor_aware_provenance.json'
+        corrected_rows = rows(corrected) if corrected.is_file() else []
+        if (not corrected_provenance.is_file() or not corrected_rows or
+                {(r.get('cohort'), r.get('draw')) for r in corrected_rows} != expected_disease or
+                any(r.get('status') not in ('ok', 'not_estimable') for r in corrected_rows)):
+            gaps.append('Figure 4 corrected donor-aware disease signal is absent or incomplete')
+    for filename in FINAL_FIGURES:
+        if not (ROOT / 'figures' / filename).is_file():
+            gaps.append(f'missing strict figure: {filename}')
+    return gaps, readiness
+
+
+def numeric_summary(table: list[dict], keys: tuple[str, ...], metrics: tuple[str, ...]) -> str:
+    """Render observed means only; no unsupported ordering or P value."""
+    data: dict[tuple[str, ...], dict[str, list[float]]] = defaultdict(lambda: defaultdict(list))
+    for row in table:
+        group = tuple(row[k] for k in keys)
+        for metric in metrics:
+            try:
+                value = float(row[metric])
+            except (KeyError, ValueError, TypeError):
+                continue
+            if value == value and value not in (float('inf'), float('-inf')):
+                data[group][metric].append(value)
+    lines = []
+    for group, values in sorted(data.items()):
+        parts = [f'{key}={value}' for key, value in zip(keys, group)]
+        parts += [f'{metric}={sum(items)/len(items):.3f} (n={len(items)})'
+                  for metric, items in values.items() if items]
+        lines.append('; '.join(parts).replace('_', r'\_') + r'\par')
+    return '\n'.join(lines)
+
+
+def complete_results() -> None:
+    """Fill only numbers present in verified strict CSVs; leave no preview placeholders."""
+    additions = {
+        2: ('source_data/fig2_strict_curve.csv', ('n_pairs', 'arm'), ('precision', 'coverage', 'comp_l1')),
+        3: ('source_data/fig3_per_sample.csv', ('arm',), ('precision', 'coverage', 'comp_l1')),
+        4: ('source_data/fig4_strict_per_sample.csv', ('cohort', 'arm'), ('pb_r', 'comp_l1')),
+        5: ('source_data/rare_summary.csv', ('cohort', 'arm'), ('mae_donor_pp', 'generated_zero_donors')),
+    }
+    openers = {
+        2: (r'\subsection*{Pretraining design and strict paired-support curve}' '\n'
+            'The held-out native-pseudobulk precision and coverage ablations use the '
+            'common 1,006-gene rescore described in Methods. Architecture and gene-panel '
+            'families have different training detection floors. The nested ImMicro curve '
+            'uses five outer folds and $n=5,10,20,40$ distinct training donors per fold. '
+            'Historical rank and full-parameter five-fold results are reported separately.\n'),
+        3: (r'\subsection*{Healthy generation with exact five-pair support}' '\n'
+            'Each ImMicro outer fold uses one matched sample from each of five training '
+            'donors for LoRA, paired calibration and scSemiProfiler. The remaining donors '
+            'are evaluated on common observed cells, measured genes and frozen labels. '
+            'Figure~\\ref{fig:fig3} displays the strict quality measures and operational '
+            'time, which excludes population pretraining.\n'),
+        4: (r'\subsection*{Disease comparisons with exact five-pair support}' '\n'
+            'Each of four disease cohorts contributes five frozen draws. One earliest '
+            'identity-passed matched-stratum visit per selected donor trains all arms; '
+            'other visits of that donor are excluded. Donor-aware disease contrasts and '
+            'deconvolution are scored on the common held-out support. The old five-fold '
+            'analysis remains a separate historical sensitivity analysis.\n'),
+        5: (r'\subsection*{Rare states with paired support}' '\n'
+            'All four disease cohorts and five draws use the exact same five-pair supports '
+            'as Figure~\\ref{fig:fig4}. Zero-generated-state draws remain in every '
+            'aggregate, required-marker failures make a state ineligible, and repeated '
+            'visits are clustered by donor. The unmatched Beh\\c{c}et analysis is '
+            'descriptive and separate.\n'),
+    }
+    for number, (source, keys, metrics) in additions.items():
+        path = STAGE / 'sections' / f'results_fig{number}.tex'
+        text = openers[number]
+        text += ('\n\\textbf{Measured strict-support summary.} Values below are arithmetic means '
+                 'of the named source-data rows; $n$ counts rows, not independent donors. '
+                 'Donor-cluster uncertainty and formal comparisons require the separate '
+                 'statistics receipts.\\par\n')
+        text += numeric_summary(rows(ROOT / source), keys, metrics) + '\n'
+        if number == 2:
+            text += ('\nComposition was evaluated on exactly the same selected cells and Poisson '
+                     'counts as the pretraining precision/coverage comparison, using the frozen '
+                     'AIFI annotator. The original logFC and top-DEG ablation panels are retained '
+                     'separately with their original epoch, readout and seed budgets; their '
+                     'absolute scores are not mixed with the new rescore.\\par\n')
+            text += numeric_summary(rows(ROOT / 'source_data/ablation_pretrain_composition_summary.csv'),
+                                    ('family', 'method'), ('comp_l1_mean',)) + '\n'
+        if number == 3:
+            extras = []
+            for record in rows(ROOT / 'source_data/fig3_extras.csv'):
+                if record.get('table') == 'metrics.csv' and record.get('mode') == 'raw':
+                    extras.append({'arm': record.get('set', ''), **record})
+                elif (record.get('table') == 'en.csv' and record.get('cellset') == 'pc'
+                      and record.get('distance') == 'sq'):
+                    extras.append({'arm': record.get('set', ''), **record})
+            text += ('\n\\textbf{Realism and operational time.} C2ST AUC, MMD$^2$ '
+                     'and $E_N$ are computed from the strict extras; time is fine-tuning '
+                     'plus inference seconds, with pretraining excluded.\\par\n')
+            text += numeric_summary(extras, ('arm',), ('c2st_rf_auc', 'mmd2_sum', 'en')) + '\n'
+            text += numeric_summary(rows(ROOT / 'source_data/fig3_runtime.csv'),
+                                    ('arm',), ('operational_seconds',)) + '\n'
+        if number == 4:
+            donor_aware = [r for r in rows(ROOT / 'source_data/fig4_donor_aware_signal.csv')
+                           if r.get('status') == 'ok']
+            text += ('\n\\textbf{Primary donor-aware disease signal.} Equal-patient '
+                     'condition contrasts, with repeated visits collapsed by donor and '
+                     'condition, are reported by cohort, arm, cell type and draw. '
+                     'A missing population is marked not estimable and contributes no '
+                     'fabricated zero. The values below summarize estimable rows; '
+                     'patient-cluster intervals are in the accompanying source tables.\\par\n')
+            text += numeric_summary(donor_aware, ('cohort', 'arm'),
+                                    ('pearson_r', 'partial_r', 'cat50', 'limma_top50')) + '\n'
+            contrast = [r for r in rows(ROOT / 'source_data/fig4_strict_contrast.csv')
+                        if r.get('table') == 'headline.csv']
+            text += ('\n\\textbf{Historical contrast sensitivity.} The legacy per-sample '
+                     'logFC, CAT and limma headline values below retain their original '
+                     'independent-sample definition. They are separate from corrected '
+                     'donor-aware disease signal.\\par\n')
+            text += numeric_summary(contrast, ('cohort', 'arm'),
+                                    ('partial_r', 'cat50', 'limma_top50')) + '\n'
+            text += ('\n\\textbf{Cross-draw uncertainty.} Donor-cluster confidence intervals '
+                     'over all five verified draws, with repeated visits and draw membership '
+                     'kept together, are supplied in '
+                     '\\texttt{fig4\\_cross\\_draw\\_donor\\_ci.csv}.\\par\n')
+            text += ('\n\\textbf{Same-support deconvolution.} Deconvolution '
+                     'provides fractions and supported cell-type expression, not '
+                     'generated-cell realism scores.\\par\n')
+            text += numeric_summary(rows(ROOT / 'source_data/fig4_deconvolution.csv'),
+                                    ('cohort', 'arm'), ('composition_l1',)) + '\n'
+        path.write_text(text)
+    path = STAGE / 'sections/discussion.tex'
+    path.write_text('\\section*{Discussion}\n'
+                    'The strict-support numerical summaries in Figs~2--5 report the completed '
+                    'five-pair design. They should be interpreted with their donor-cluster '
+                    'uncertainty and source tables; row counts are not biological replicates. '
+                    'Historical five-fold and unmatched Beh\\c{c}et analyses remain separate. '
+                    'Figure~\\ref{fig:fig6} awaits the user-prepared bulk-only reproduction data.\n')
+
+
+def copy_source_files() -> dict[str, str]:
+    before = {}
+    for rel in tracked_sources():
+        src, dst = CANON / rel, STAGE / rel
+        if not src.is_file():
+            raise ValueError(f'tracked source missing: {src}')
+        before[str(rel)] = digest(src)
+        dst.parent.mkdir(parents=True, exist_ok=True)
+        shutil.copy2(src, dst)
+    return before
+
+
+def edit_method_model() -> None:
+    path = STAGE / 'sections/methods_model.tex'
+    body = path.read_text().split('\\subsection*{SLE benchmark and frozen cell-type annotator}')[0]
+    body = body.replace('Fig.~\\ref{fig:fig1}b', 'Fig.~\\ref{fig:fig1}')
+    body = body.replace('Fig.~\\ref{fig:fig1}a', 'Fig.~\\ref{fig:fig1}')
+    body = body.replace('Fig.~\\ref{fig:fig1}c', 'Fig.~\\ref{fig:fig1}')
+    body = body.replace('Fig.~\\ref{fig:fig1}d', 'Fig.~\\ref{fig:fig1}')
+    body = body.replace('Fig.~\\ref{fig:fig1}f', 'Fig.~\\ref{fig:fig2}')
+    body = re.sub(r'It produced every generated cell set in this study except the threshold-read-out sets.*?Unless stated otherwise',
+                  'The pretraining design rescoring in Fig.~\\\\ref{fig:fig2} uses saved epoch-16 Bernoulli outputs. Unless stated otherwise',
+                  body, flags=re.S)
+    body += '\n\\subsection*{Held-out pretraining design rescore}\n'
+    body += ('Saved architecture and gene-panel outputs for the 42 held-out SLE donors were rescored '
+             'separately. On the common 1,006-gene axis, each donor contributed 100 real reference cells, '
+             '100 disjoint real query cells and 100 generated cells per arm. One fixed Poisson read-out, '
+             'a real-reference 50-component PCA and $k=10$ local neighbourhoods defined precision and '
+             'coverage. The architecture and panel families had different training detection floors and '
+             'are not a factorial comparison. One saved generation seed per arm makes these descriptive scores.\n')
+    path.write_text(body)
+
+
+def overlay(final: bool) -> list[str]:
+    changed = []
+    for src in sorted((EDITS / 'sections').glob('*.tex')):
+        dst = STAGE / 'sections' / src.name
+        shutil.copy2(src, dst)
+        changed.append(str(dst.relative_to(STAGE)))
+    edit_method_model()
+    changed.append('sections/methods_model.tex')
+    main = STAGE / 'main.tex'
+    content = main.read_text()
+    content = content.replace('% Overleaf main document.', '% RESTRUCTURING DRAFT: strict Figures 3--5 remain pending.\n% Overleaf main document.', 1)
+    content = content.replace('% Figures with their legends, each on its own page(s). Panels are the deck\'s vector graphics, placed as-is;\n% the 180 mm journal layout is still to be drawn.',
+                              '% Figure 1--5 restructuring draft; strict missing panels are explicitly labelled.')
+    if final:
+        content = content.replace('% RESTRUCTURING DRAFT: strict Figures 3--5 remain pending.\n', '')
+    else:
+        content = content.replace('\\maketitle',
+            '\\maketitle\n\\noindent\\fcolorbox{red}{white}{\\parbox{0.92\\textwidth}{'
+            '\\textbf{RESTRUCTURING DRAFT.} Strict five-pair results for Figs 2--5 '
+            'are incomplete. The approved title, abstract and Introduction retain their '
+            'original wording and must be rereviewed against final strict results.}}\\par\\medskip', 1)
+    main.write_text(content)
+    changed.append('main.tex')
+    supp = STAGE / 'supplementary.tex'
+    supp_text = supp.read_text()
+    supp_text = supp_text.replace('\\begin{document}',
+        '\\begin{document}\n\\noindent\\textcolor{red}{[HISTORICAL SUPPLEMENTARY DRAFT: '
+        'legacy analyses have not been reconciled with exact-five-pair support.]}\\par\\medskip', 1)
+    supp.write_text(supp_text)
+    changed.append('supplementary.tex')
+    figures = dict(FIGURES)
+    if final:
+        complete_results()
+        (STAGE / 'sections/fig2.tex').write_text(
+            '\\mainfigure{fig:fig2}{Pretraining design, real-bulk adaptation and exact paired-data budgets}\n'
+            '\\figpanelh{}{figures/strict_20261012/fig2_ablation_and_support.pdf}{0.80}\n'
+            '\\figlegend{Native pseudobulk architecture and panel sweeps use the same held-out '
+            'donors, measured genes and readout within each sweep; the 1\\% and 0.1\\% training '
+            'floors are distinct experiments. Composition uses the same selected cells and frozen '
+            'annotator. Full fine-tuning and LoRA ranks 4, 16 and 64 use matched real-bulk '
+            'five-fold train/validation/test sets. Rank 16 is the quality--parameter-budget choice, '
+            'not the best on every metric. Strict learning curves use exactly 5, 10, 20 or 40 '
+            'different donor/sample pairs, fixed 3,000 LoRA updates and no extra validation pairs. '
+            'Raw and external AIFI calibration use zero target paired single-cell samples. '
+            'Foldwise points and means are descriptive; generated cells are not independent donors.}\n'
+            '\\figpanelh{Historical architecture logFC/DEG benchmark; original protocol}{figures/deck_20261010/sec03_width_bench.pdf}{0.44}\n'
+            '\\figpanelh{Historical gene-panel logFC/DEG benchmark; original protocol}{figures/deck_20261010/sec03_panel.pdf}{0.44}\n'
+            '\\figlegend{These historical panels retain their original epoch aggregation, readouts '
+            'and unequal available generation-seed budgets. They connect the expression/DEG '
+            'endpoints to the newly rescored geometry and composition endpoints, but are not '
+            'same-protocol numerical comparisons with the panels above.}\n')
+        changed.append('sections/fig2.tex')
+        figures.update(FINAL_FIGURES)
+        strict_figures = {
+            'fig3': ('Healthy exact five-pair OOF', 'fig3_healthy_strict_oof.pdf'),
+            'fig4': ('Disease exact five-pair draws', 'fig4_disease_strict_draws.pdf'),
+            'fig5': ('Paired rare states under exact five-pair support', 'fig5_rare_states_strict.pdf'),
+        }
+        for name, (title, filename) in strict_figures.items():
+            p = STAGE / 'sections' / f'{name}.tex'
+            panels = f'\\figpanelh{{}}{{figures/strict_20261012/{filename}}}{{0.77}}\n'
+            if name == 'fig3':
+                panels += ('\\figpanelh{}{figures/strict_20261012/fig3_realism_metrics.pdf}{0.38}\n')
+                panels += ('\\figpanelh{}{figures/strict_20261012/fig3_canonical_marker_dotplot.pdf}{0.42}\n')
+                for extra in ('umap_by_celltype','composition_fractions','runtime_components'):
+                    panels += f'\\figpanelh{{}}{{figures/strict_20261012/fig3_{extra}.pdf}}{{0.62}}\n'
+            if name == 'fig4':
+                panels += ('\\figpanelh{}{figures/strict_20261012/fig4_disease_signal_strict.pdf}{0.48}\n'
+                           '\\figpanelh{}{figures/strict_20261012/fig4_deconvolution_strict.pdf}{0.42}\n'
+                           '\\figpanelh{}{figures/strict_20261012/fig4_deconvolution_expression_strict.pdf}{0.48}\n')
+                panels += ('\\figpanelh{}{figures/strict_20261012/fig4_historical_5fold_separate.pdf}{0.38}\n')
+                for extra in ('scatter','heatmap','cat'):
+                    panels += f'\\figpanelh{{}}{{figures/strict_20261012/fig4_disease_signal_{extra}.pdf}}{{0.60}}\n'
+            if name == 'fig5':
+                for extra in ('rare_visuals','all_states','behcet_rules'):
+                    panels += f'\\figpanelh{{}}{{figures/strict_20261012/fig5_{extra}_strict.pdf}}{{0.72}}\n'
+            p.write_text(f'\\mainfigure{{fig:{name}}}{{{title}}}\n' + panels +
+                         '\\figlegend{Strict-support results and source-data tables are '
+                         'reported in the corresponding Results section. Figure 4 historical '
+                         'five-fold values appear in a separate labelled panel.}\n')
+    for source, target in figures.items():
+        src = ROOT / 'figures' / source
+        if not src.is_file():
+            raise ValueError(f'missing figure: {src}')
+        dst = STAGE / 'figures/strict_20261012' / target
+        dst.parent.mkdir(parents=True, exist_ok=True)
+        shutil.copy2(src, dst)
+        changed.append(str(dst.relative_to(STAGE)))
+    evidence = ('source_data/fig1_corpus_aggregates.json',
+                'source_data/ablation_pretrain_pc.csv',
+                'source_data/ablation_pretrain_pc_receipt.json',
+                'source_data/fig2_historical_rank_full.csv',
+                'source_data/fig4_historical_5fold.csv',
+                'reports/figure1_provenance.json',
+                'reports/figures234_readiness.json',
+                'reports/rare_provenance.json')
+    if final:
+        evidence += ('source_data/fig2_strict_curve.csv',
+                     'source_data/fig3_per_sample.csv',
+                     'source_data/fig3_extras.csv',
+                     'source_data/fig3_runtime.csv',
+                     'source_data/fig3_runtime.json',
+                     'source_data/fig3_visual_data.json',
+                     'source_data/fig4_strict_per_sample.csv',
+                     'source_data/fig4_corrected_statistics.csv',
+                     'source_data/fig4_cross_draw_donor_ci.csv',
+                     'source_data/fig4_cross_draw_donor_ci.json',
+                     'source_data/fig4_donor_aware_signal.csv',
+                     'source_data/fig4_donor_aware_summary.csv',
+                     'source_data/fig4_donor_aware_genes.csv',
+                     'source_data/fig4_donor_aware_cat.csv',
+                     'source_data/fig4_donor_aware_provenance.json',
+                     'source_data/fig4_strict_contrast.csv',
+                     'source_data/fig4_deconvolution.csv',
+                     'source_data/fig4_deconvolution_signal.csv',
+                     'source_data/rare_summary.csv',
+                     'source_data/rare_ineligible_states.csv',
+                     'source_data/rare_behcet_descriptive.csv')
+    for rel in evidence:
+        src = ROOT / rel
+        if not src.is_file():
+            raise ValueError(f'missing source data: {src}')
+        dst = STAGE / 'strict_20261012' / rel
+        dst.parent.mkdir(parents=True, exist_ok=True)
+        shutil.copy2(src, dst)
+        changed.append(str(dst.relative_to(STAGE)))
+    changed.extend(['sections/fig1.tex', 'sections/fig2.tex', 'sections/fig3.tex',
+                    'sections/fig4.tex', 'sections/fig5.tex'])
+    return sorted(set(changed))
+
+
+def verify_unchanged_frontmatter(original: dict[str, str]) -> None:
+    for name in ('sections/abstract.tex', 'sections/introduction.tex', 'authors.tex'):
+        if digest(STAGE / name) != original[name]:
+            raise ValueError(f'user-approved frontmatter changed: {name}')
+    canonical_main = (CANON / 'main.tex').read_text()
+    staged_main = (STAGE / 'main.tex').read_text()
+    for pattern in (r'\\title\{[^\n]+', r'\\abstract\{[^\n]+'):
+        if re.search(pattern, canonical_main).group() != re.search(pattern, staged_main).group():
+            raise ValueError(f'user-approved title or abstract command changed: {pattern}')
+
+
+def allowed_frontmatter_refresh(previous: dict[str, str], current: dict[str, str],
+                                *, old_main: str | None = None, new_main: str | None = None) -> dict:
+    """Permit only new approved Title, Abstract and Introduction source text."""
+    changed = {name: {'previous_sha256': old, 'current_sha256': current.get(name)}
+               for name, old in previous.items() if current.get(name) != old}
+    allowed = {'main.tex', 'sections/abstract.tex', 'sections/introduction.tex'}
+    extra = set(changed) - allowed
+    if extra:
+        raise ValueError(f'canonical source changed outside approved frontmatter: {sorted(extra)}')
+    if 'main.tex' in changed:
+        if old_main is None or new_main is None:
+            raise ValueError('main.tex changed beyond approved title/abstract commands')
+        pattern = r'\\(?:title|abstract)\{[^\n]*\}'
+        if re.sub(pattern, r'\\frontmatter{APPROVED}', old_main) != re.sub(
+                pattern, r'\\frontmatter{APPROVED}', new_main):
+            raise ValueError('main.tex changed beyond approved title/abstract commands')
+    return changed
+
+
+def main() -> None:
+    p = argparse.ArgumentParser(description=__doc__)
+    mode = p.add_mutually_exclusive_group(required=True)
+    mode.add_argument('--preview', action='store_true')
+    mode.add_argument('--require-complete', action='store_true')
+    args = p.parse_args()
+    if subprocess.check_output(['git', '-C', str(CANON), 'status', '--porcelain']).strip():
+        raise SystemExit('canonical manuscript is not clean; refusing to assemble')
+    checked_provenance(ROOT / 'reports/figure1_provenance.json', 'Figure 1')
+    pretrain = checked_provenance(ROOT / 'source_data/ablation_pretrain_pc_receipt.json', 'Figure 2 P/C')
+    recipe = pretrain.get('recipe', {})
+    if (pretrain.get('schema') != 'pbisc.fig2.pretrain_pc.v1' or
+            recipe.get('n_pcs') != 50 or recipe.get('local_k') != 10 or
+            pretrain.get('gene_axis', {}).get('n') != 1006 or
+            {r['family'] for r in rows(ROOT / 'source_data/ablation_pretrain_pc.csv')} !=
+            {'architecture_floor1pct', 'panel_floor0.1pct'}):
+        raise SystemExit('Figure 2 measured P/C receipt or source table differs from the frozen rescore')
+    gaps, readiness = strict_gate()
+    if args.require_complete and gaps:
+        raise SystemExit('final assembly refused:\n- ' + '\n- '.join(sorted(set(gaps))))
+    previous = STAGE / 'integration_manifest.json'
+    refreshed = {}
+    if previous.is_file() and args.require_complete:
+        prior = document(previous)
+        old = prior.get('canonical_source_sha256', {})
+        current = {rel: digest(CANON / rel) if (CANON / rel).is_file() else None for rel in old}
+        old_main = None
+        if current.get('main.tex') != old.get('main.tex'):
+            old_head = prior.get('canonical_head')
+            if not old_head:
+                raise SystemExit('review preview has no canonical head for frontmatter comparison')
+            old_main = subprocess.check_output(['git', '-C', str(CANON), 'show',
+                                                f'{old_head}:main.tex'], text=True)
+        try:
+            refreshed = allowed_frontmatter_refresh(old, current, old_main=old_main,
+                                                    new_main=(CANON / 'main.tex').read_text())
+        except ValueError as exc:
+            raise SystemExit(str(exc)) from exc
+    originals = copy_source_files()
+    changed = overlay(args.require_complete)
+    verify_unchanged_frontmatter(originals)
+    # Keep the original claims available for review without placing them in Results.
+    legacy = STAGE / 'editorial/legacy_results'
+    legacy.mkdir(parents=True, exist_ok=True)
+    for name in ('results_fig1', 'results_fig2', 'results_fig3', 'results_fig4',
+                 'results_fig5', 'results_fig6', 'methods_paired', 'methods_eval', 'discussion'):
+        src = CANON / 'sections' / f'{name}.tex'
+        shutil.copy2(src, legacy / src.name)
+        changed.append(str((legacy / src.name).relative_to(STAGE)))
+    manifest = {
+        'schema': 'pbisc.paper.manuscript-integration.v1',
+        'mode': 'complete' if args.require_complete else 'restructuring_preview',
+        'canonical_root': str(CANON), 'stage_root': str(STAGE),
+        'canonical_head': subprocess.check_output(['git', '-C', str(CANON), 'rev-parse', 'HEAD'], text=True).strip(),
+        'canonical_source_sha256': originals,
+        'approved_frontmatter_refresh': refreshed,
+        'staged_changes': {rel: {'sha256': digest(STAGE / rel),
+                                 'canonical_sha256': originals.get(rel)} for rel in changed},
+        'figure_source_sha256': {name: digest(ROOT / 'figures' / name) for name in
+                                 (FIGURES | (FINAL_FIGURES if args.require_complete else {}))},
+        'readiness': readiness,
+        'gaps': gaps,
+        'figure6': 'waiting_user_prepared_data; unchanged placeholder',
+        'git_push': False, 'overleaf_sync': False,
+    }
+    previous.write_text(json.dumps(manifest, indent=2) + '\n')
+    print(json.dumps({'mode': manifest['mode'], 'staged_changed_files': len(changed),
+                      'gaps': gaps, 'manifest': str(previous)}, indent=2))
+
+
+if __name__ == '__main__':
+    main()

paper-releases/pbisc-diffusion/updates/20261012T131501Z-strictpairs-final-caption/diffusion/dataset/server_1/model8/plans/paper_figures_strictpairs_20261012/archive/20261012T131501Z-strictpairs-final-caption/assemble_manuscript_before_final_caption_fix.py

@@ -0,0 +1,565 @@
+#!/usr/bin/env python3
+"""Stage the PBISC-Diffusion Figure 1--5 manuscript without changing its Git tree.
+
+--preview emits an explicitly incomplete review draft. --require-complete refuses
+until every strict unit and its source binding has been verified, then uses the
+same staged file map. No Git, archive or network write is performed here.
+"""
+from __future__ import annotations
+
+import argparse
+import csv
+import hashlib
+import json
+import re
+import shutil
+import subprocess
+from collections import defaultdict
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parents[1]
+CANON = Path('/home/sj_server_1/PBISC/paper-release-20260928/manuscript')
+STAGE = ROOT / 'manuscript'
+EDITS = STAGE / 'edits'
+COHORTS = ('ye2026_sepsis', 'imperial_eskd', 'giroux2022', 'ji2025_chili')
+FIGURES = {
+    'fig1_overview.pdf': 'fig1_overview.pdf',
+    'fig2_ablation_and_support.pdf': 'fig2_ablation_and_support.pdf',
+    'fig4_historical_5fold_separate.pdf': 'fig4_historical_5fold_separate.pdf',
+}
+FINAL_FIGURES = {
+    'fig3_healthy_strict_oof.pdf': 'fig3_healthy_strict_oof.pdf',
+    'fig3_realism_metrics.pdf': 'fig3_realism_metrics.pdf',
+    'fig3_canonical_marker_dotplot.pdf': 'fig3_canonical_marker_dotplot.pdf',
+    'fig3_umap_by_celltype.pdf': 'fig3_umap_by_celltype.pdf',
+    'fig3_composition_fractions.pdf': 'fig3_composition_fractions.pdf',
+    'fig3_runtime_components.pdf': 'fig3_runtime_components.pdf',
+    'fig4_disease_strict_draws.pdf': 'fig4_disease_strict_draws.pdf',
+    'fig4_disease_signal_strict.pdf': 'fig4_disease_signal_strict.pdf',
+    'fig4_disease_signal_scatter.pdf': 'fig4_disease_signal_scatter.pdf',
+    'fig4_disease_signal_heatmap.pdf': 'fig4_disease_signal_heatmap.pdf',
+    'fig4_disease_signal_cat.pdf': 'fig4_disease_signal_cat.pdf',
+    'fig4_deconvolution_strict.pdf': 'fig4_deconvolution_strict.pdf',
+    'fig4_deconvolution_expression_strict.pdf': 'fig4_deconvolution_expression_strict.pdf',
+    'fig5_rare_states_strict.pdf': 'fig5_rare_states_strict.pdf',
+    'fig5_rare_visuals_strict.pdf': 'fig5_rare_visuals_strict.pdf',
+    'fig5_all_states_strict.pdf': 'fig5_all_states_strict.pdf',
+    'fig5_behcet_rules_strict.pdf': 'fig5_behcet_rules_strict.pdf',
+}
+
+
+def digest(path: Path) -> str:
+    h = hashlib.sha256()
+    with path.open('rb') as f:
+        for chunk in iter(lambda: f.read(1024 * 1024), b''):
+            h.update(chunk)
+    return h.hexdigest()
+
+
+def document(path: Path) -> dict:
+    return json.loads(path.read_text())
+
+
+def rows(path: Path) -> list[dict[str, str]]:
+    with path.open(newline='') as f:
+        return list(csv.DictReader(f))
+
+
+def tracked_sources() -> list[Path]:
+    raw = subprocess.check_output(['git', '-C', str(CANON), 'ls-files', '-z'])
+    paths = [Path(p.decode()) for p in raw.split(b'\0') if p]
+    wanted = {'.tex', '.bib', '.cls', '.bst'}
+    return [p for p in paths if p.suffix in wanted or
+            (p.parts[0] == 'figures' and p.suffix.lower() in {'.pdf', '.png'})]
+
+
+def checked_provenance(path: Path, label: str) -> dict:
+    if not path.is_file():
+        raise ValueError(f'{label}: missing {path}')
+    item = document(path)
+    for entry in item.get('sources', []) + item.get('outputs', []):
+        source = Path(entry['path'])
+        if not source.is_file() or digest(source) != entry['sha256']:
+            raise ValueError(f'{label}: source/output hash mismatch: {source}')
+    return item
+
+
+def strict_gate() -> tuple[list[str], dict]:
+    gaps = []
+    readiness_path = ROOT / 'reports/figures234_readiness.json'
+    readiness = document(readiness_path) if readiness_path.is_file() else {}
+    if readiness.get('schema') != 'pbisc.paper.figures234.v1' or readiness.get('status') != 'complete':
+        gaps.append('Figures 2--4 readiness is not complete')
+    f2, f3, f4 = (readiness.get(k, {}) for k in ('figure2', 'figure3', 'figure4'))
+    if f2.get('strict_complete_units') != 20 or f2.get('strict_missing') or not f2.get('pretrain_composition_ready'):
+        gaps.append('Figure 2 needs 20/20 strict healthy support units')
+    if (f3.get('strict_complete_folds') != 5 or not f3.get('visual_export_ready') or
+            not f3.get('extras_complete') or not f3.get('runtime_ready')):
+        gaps.append('Figure 3 needs 5/5 folds, visual, extras and time receipts')
+    if (set(f4.get('strict_complete_draws', {})) != set(COHORTS) or
+            any(f4['strict_complete_draws'].get(c) != 5 for c in COHORTS) or
+            any(f4.get(k) for k in ('contrast_missing', 'deconvolution_missing',
+                                    'deconvolution_signal_missing'))):
+        gaps.append('Figure 4 needs 5/5 strict draws per cohort and contrast/deconvolution evidence')
+    expected_healthy = {(f'fold{fold}', n) for fold in range(5) for n in (5, 10, 20, 40)}
+    expected_disease = {(c, f'draw{draw}') for c in COHORTS for draw in range(5)}
+    curve = rows(ROOT / 'source_data/fig2_strict_curve.csv')
+    if {(r['fold'], int(r['n_pairs'])) for r in curve} != expected_healthy:
+        gaps.append('Figure 2 strict CSV has incomplete fold/size units')
+    healthy = rows(ROOT / 'source_data/fig3_per_sample.csv')
+    if {r['fold'] for r in healthy} != {f'fold{n}' for n in range(5)}:
+        gaps.append('Figure 3 strict per-sample CSV has incomplete folds')
+    disease = rows(ROOT / 'source_data/fig4_strict_per_sample.csv')
+    if {(r['cohort'], r['draw']) for r in disease} != expected_disease or any(
+            r.get('design') != 'strict_exact5_donor_draw' for r in disease):
+        gaps.append('Figure 4 strict CSV has incomplete or mixed-design draws')
+    for filename, table in [('fig2_strict_curve.csv', curve), ('fig3_per_sample.csv', healthy),
+                            ('fig4_strict_per_sample.csv', disease)]:
+        if not table or any(not r.get('support_sha256') for r in table):
+            gaps.append(f'{filename} lacks source-bound support hashes')
+    for record in curve + healthy + disease:
+        source = record.get('summary')
+        source_hash = record.get('summary_sha256')
+        if source and source_hash and (not Path(source).is_file() or digest(Path(source)) != source_hash):
+            gaps.append(f'score summary hash mismatch: {source}')
+            break
+    for table, kind in ((curve, 'healthy'), (healthy, 'healthy'), (disease, 'disease')):
+        for record in table:
+            cohort = record.get('cohort', 'immicro')
+            unit = record.get('fold') if kind == 'healthy' else record.get('draw')
+            suffix = f'{unit}/n{record["n_pairs"]}' if table is curve else (
+                f'{unit}/n5' if kind == 'healthy' else unit)
+            support = ROOT / 'protocol/splits' / cohort / kind / suffix / 'support.json'
+            if not support.is_file() or document(support).get('sha256') != record.get('support_sha256'):
+                gaps.append(f'{cohort}/{kind}/{suffix}: source support mismatch')
+                break
+            summary = ROOT / 'scores' / cohort / kind / suffix / 'score/summary.json'
+            score_sha = record.get('score_sha256') or record.get('summary_sha256')
+            if not summary.is_file() or digest(summary) != score_sha:
+                gaps.append(f'{cohort}/{kind}/{suffix}: score summary hash mismatch')
+                break
+    rare_path = ROOT / 'reports/rare_provenance.json'
+    rare = document(rare_path) if rare_path.is_file() else {}
+    units = rare.get('units', [])
+    if (rare.get('schema') != 'pbisc.figure5.analysis.v1' or len(units) != 20 or
+            {(u.get('cohort'), u.get('unit')) for u in units} != expected_disease or
+            any(u.get('design') != 'strict5pair' or u.get('evidence_tier') != 'strict'
+                or not u.get('support_sha256') for u in units)):
+        gaps.append('Figure 5 needs all 20 strict rare-state receipts')
+    rare_table = rows(ROOT / 'source_data/rare_summary.csv')
+    if (not rare_table or {r.get('evidence_tier') for r in rare_table} != {'strict'} or
+            {(r['cohort'], r['unit']) for r in rare_table} != expected_disease):
+        gaps.append('Figure 5 rare-state CSV is absent, diagnostic or incomplete')
+    for cohort, unit in expected_disease:
+        subset = [r for r in rare_table if r.get('cohort') == cohort and r.get('unit') == unit]
+        if {r.get('arm') for r in subset} != {'raw', 'refcal', 'pairedcal', 'scsemi', 'lora'}:
+            gaps.append(f'Figure 5 strict arms incomplete: {cohort}/{unit}')
+            break
+    for unit in units:
+        support = ROOT / 'protocol/splits' / str(unit.get('cohort')) / 'disease' / str(unit.get('unit')) / 'support.json'
+        if not support.is_file() or document(support).get('sha256') != unit.get('support_sha256'):
+            gaps.append(f'Figure 5 strict support hash mismatch: {unit.get("cohort")}/{unit.get("unit")}')
+            break
+    if readiness.get('status') == 'complete':
+        runtime = ROOT / 'source_data/fig3_runtime.csv'
+        runtime_meta = ROOT / 'source_data/fig3_runtime.json'
+        visual = ROOT / 'source_data/fig3_visual_data.npz'
+        visual_meta = ROOT / 'source_data/fig3_visual_data.json'
+        if (not runtime.is_file() or not runtime_meta.is_file() or
+                document(runtime_meta).get('csv_sha256') != digest(runtime)):
+            gaps.append('Figure 3 runtime source/receipt hash mismatch')
+        if (not visual.is_file() or not visual_meta.is_file() or
+                document(visual_meta).get('npz_sha256') != digest(visual)):
+            gaps.append('Figure 3 visual source/receipt hash mismatch')
+        extras = ROOT / 'source_data/fig3_extras.csv'
+        if not extras.is_file() or not rows(extras):
+            gaps.append('Figure 3 realism extras CSV is missing')
+        for name in ('fig4_strict_contrast.csv', 'fig4_deconvolution.csv',
+                     'fig4_deconvolution_signal.csv', 'fig4_corrected_statistics.csv',
+                     'fig4_cross_draw_donor_ci.csv', 'fig4_donor_aware_signal.csv',
+                     'fig4_donor_aware_summary.csv', 'fig4_donor_aware_genes.csv',
+                     'fig4_donor_aware_cat.csv'):
+            path = ROOT / 'source_data' / name
+            if not path.is_file() or not rows(path):
+                gaps.append(f'Figure 4 required source table missing: {name}')
+        cross = ROOT / 'source_data/fig4_cross_draw_donor_ci.csv'
+        cross_receipt = ROOT / 'source_data/fig4_cross_draw_donor_ci.json'
+        if (not cross_receipt.is_file() or not cross.is_file() or
+                document(cross_receipt).get('csv_sha256') != digest(cross) or
+                {r.get('cohort') for r in rows(cross)} != set(COHORTS)):
+            gaps.append('Figure 4 five-draw donor-cluster CI source or receipt mismatch')
+        corrected = ROOT / 'source_data/fig4_donor_aware_signal.csv'
+        corrected_provenance = ROOT / 'source_data/fig4_donor_aware_provenance.json'
+        corrected_rows = rows(corrected) if corrected.is_file() else []
+        if (not corrected_provenance.is_file() or not corrected_rows or
+                {(r.get('cohort'), r.get('draw')) for r in corrected_rows} != expected_disease or
+                any(r.get('status') not in ('ok', 'not_estimable') for r in corrected_rows)):
+            gaps.append('Figure 4 corrected donor-aware disease signal is absent or incomplete')
+    for filename in FINAL_FIGURES:
+        if not (ROOT / 'figures' / filename).is_file():
+            gaps.append(f'missing strict figure: {filename}')
+    return gaps, readiness
+
+
+def numeric_summary(table: list[dict], keys: tuple[str, ...], metrics: tuple[str, ...]) -> str:
+    """Render observed means only; no unsupported ordering or P value."""
+    data: dict[tuple[str, ...], dict[str, list[float]]] = defaultdict(lambda: defaultdict(list))
+    for row in table:
+        group = tuple(row[k] for k in keys)
+        for metric in metrics:
+            try:
+                value = float(row[metric])
+            except (KeyError, ValueError, TypeError):
+                continue
+            if value == value and value not in (float('inf'), float('-inf')):
+                data[group][metric].append(value)
+    lines = []
+    for group, values in sorted(data.items()):
+        parts = [f'{key}={value}' for key, value in zip(keys, group)]
+        parts += [f'{metric}={sum(items)/len(items):.3f} (n={len(items)})'
+                  for metric, items in values.items() if items]
+        lines.append('; '.join(parts).replace('_', r'\_') + r'\par')
+    return '\n'.join(lines)
+
+
+def complete_results() -> None:
+    """Fill only numbers present in verified strict CSVs; leave no preview placeholders."""
+    additions = {
+        2: ('source_data/fig2_strict_curve.csv', ('n_pairs', 'arm'), ('precision', 'coverage')),
+        3: ('source_data/fig3_per_sample.csv', ('arm',), ('precision', 'coverage', 'comp_l1')),
+        4: ('source_data/fig4_strict_per_sample.csv', ('cohort', 'arm'), ('pb_r', 'comp_l1')),
+        5: ('source_data/rare_summary.csv', ('cohort', 'arm'), ('mae_donor_pp', 'generated_zero_donors')),
+    }
+    openers = {
+        2: (r'\subsection*{Pretraining design and strict paired-support curve}' '\n'
+            'The held-out native-pseudobulk precision and coverage ablations use the '
+            'common 1,006-gene rescore described in Methods. Architecture and gene-panel '
+            'families have different training detection floors. The nested ImMicro curve '
+            'uses five outer folds and $n=5,10,20,40$ distinct training donors per fold. '
+            'Historical rank and full-parameter five-fold results are reported separately.\n'),
+        3: (r'\subsection*{Healthy generation with exact five-pair support}' '\n'
+            'Each ImMicro outer fold uses one matched sample from each of five training '
+            'donors for LoRA, paired calibration and scSemiProfiler. The remaining donors '
+            'are evaluated on common observed cells, measured genes and frozen labels. '
+            'Figure~\\ref{fig:fig3} displays the strict quality measures and operational '
+            'time, which excludes population pretraining.\n'),
+        4: (r'\subsection*{Disease comparisons with exact five-pair support}' '\n'
+            'Each of four disease cohorts contributes five frozen draws. One earliest '
+            'identity-passed matched-stratum visit per selected donor trains all arms; '
+            'other visits of that donor are excluded. Donor-aware disease contrasts and '
+            'deconvolution are scored on the common held-out support. The old five-fold '
+            'analysis remains a separate historical sensitivity analysis.\n'),
+        5: (r'\subsection*{Rare states with paired support}' '\n'
+            'All four disease cohorts and five draws use the exact same five-pair supports '
+            'as Figure~\\ref{fig:fig4}. Zero-generated-state draws remain in every '
+            'aggregate, required-marker failures make a state ineligible, and repeated '
+            'visits are clustered by donor. The unmatched Beh\\c{c}et analysis is '
+            'descriptive and separate.\n'),
+    }
+    for number, (source, keys, metrics) in additions.items():
+        path = STAGE / 'sections' / f'results_fig{number}.tex'
+        text = openers[number]
+        text += ('\n\\textbf{Measured strict-support summary.} Values below are arithmetic means '
+                 'of the named source-data rows; $n$ counts rows, not independent donors. '
+                 'Donor-cluster uncertainty and formal comparisons require the separate '
+                 'statistics receipts.\\par\n')
+        text += numeric_summary(rows(ROOT / source), keys, metrics) + '\n'
+        if number == 3:
+            extras = []
+            for record in rows(ROOT / 'source_data/fig3_extras.csv'):
+                if record.get('table') == 'metrics.csv' and record.get('mode') == 'raw':
+                    extras.append({'arm': record.get('set', ''), **record})
+                elif (record.get('table') == 'en.csv' and record.get('cellset') == 'pc'
+                      and record.get('distance') == 'sq'):
+                    extras.append({'arm': record.get('set', ''), **record})
+            text += ('\n\\textbf{Realism and operational time.} C2ST AUC, MMD$^2$ '
+                     'and $E_N$ are computed from the strict extras; time is fine-tuning '
+                     'plus inference seconds, with pretraining excluded.\\par\n')
+            text += numeric_summary(extras, ('arm',), ('c2st_rf_auc', 'mmd2_sum', 'en')) + '\n'
+            text += numeric_summary(rows(ROOT / 'source_data/fig3_runtime.csv'),
+                                    ('arm',), ('operational_seconds',)) + '\n'
+        if number == 4:
+            donor_aware = [r for r in rows(ROOT / 'source_data/fig4_donor_aware_signal.csv')
+                           if r.get('status') == 'ok']
+            text += ('\n\\textbf{Primary donor-aware disease signal.} Equal-patient '
+                     'condition contrasts, with repeated visits collapsed by donor and '
+                     'condition, are reported by cohort, arm, cell type and draw. '
+                     'A missing population is marked not estimable and contributes no '
+                     'fabricated zero. The values below summarize estimable rows; '
+                     'patient-cluster intervals are in the accompanying source tables.\\par\n')
+            text += numeric_summary(donor_aware, ('cohort', 'arm'),
+                                    ('pearson_r', 'partial_r', 'cat50', 'limma_top50')) + '\n'
+            contrast = [r for r in rows(ROOT / 'source_data/fig4_strict_contrast.csv')
+                        if r.get('table') == 'headline.csv']
+            text += ('\n\\textbf{Historical contrast sensitivity.} The legacy per-sample '
+                     'logFC, CAT and limma headline values below retain their original '
+                     'independent-sample definition. They are separate from corrected '
+                     'donor-aware disease signal.\\par\n')
+            text += numeric_summary(contrast, ('cohort', 'arm'),
+                                    ('partial_r', 'cat50', 'limma_top50')) + '\n'
+            text += ('\n\\textbf{Cross-draw uncertainty.} Donor-cluster confidence intervals '
+                     'over all five verified draws, with repeated visits and draw membership '
+                     'kept together, are supplied in '
+                     '\\texttt{fig4\\_cross\\_draw\\_donor\\_ci.csv}.\\par\n')
+            text += ('\n\\textbf{Same-support deconvolution.} Deconvolution '
+                     'provides fractions and supported cell-type expression, not '
+                     'generated-cell realism scores.\\par\n')
+            text += numeric_summary(rows(ROOT / 'source_data/fig4_deconvolution.csv'),
+                                    ('cohort', 'arm'), ('composition_l1',)) + '\n'
+        path.write_text(text)
+    path = STAGE / 'sections/discussion.tex'
+    path.write_text('\\section*{Discussion}\n'
+                    'The strict-support numerical summaries in Figs~2--5 report the completed '
+                    'five-pair design. They should be interpreted with their donor-cluster '
+                    'uncertainty and source tables; row counts are not biological replicates. '
+                    'Historical five-fold and unmatched Beh\\c{c}et analyses remain separate. '
+                    'Figure~\\ref{fig:fig6} awaits the user-prepared bulk-only reproduction data.\n')
+
+
+def copy_source_files() -> dict[str, str]:
+    before = {}
+    for rel in tracked_sources():
+        src, dst = CANON / rel, STAGE / rel
+        if not src.is_file():
+            raise ValueError(f'tracked source missing: {src}')
+        before[str(rel)] = digest(src)
+        dst.parent.mkdir(parents=True, exist_ok=True)
+        shutil.copy2(src, dst)
+    return before
+
+
+def edit_method_model() -> None:
+    path = STAGE / 'sections/methods_model.tex'
+    body = path.read_text().split('\\subsection*{SLE benchmark and frozen cell-type annotator}')[0]
+    body = body.replace('Fig.~\\ref{fig:fig1}b', 'Fig.~\\ref{fig:fig1}')
+    body = body.replace('Fig.~\\ref{fig:fig1}a', 'Fig.~\\ref{fig:fig1}')
+    body = body.replace('Fig.~\\ref{fig:fig1}c', 'Fig.~\\ref{fig:fig1}')
+    body = body.replace('Fig.~\\ref{fig:fig1}d', 'Fig.~\\ref{fig:fig1}')
+    body = body.replace('Fig.~\\ref{fig:fig1}f', 'Fig.~\\ref{fig:fig2}')
+    body = re.sub(r'It produced every generated cell set in this study except the threshold-read-out sets.*?Unless stated otherwise',
+                  'The pretraining design rescoring in Fig.~\\\\ref{fig:fig2} uses saved epoch-16 Bernoulli outputs. Unless stated otherwise',
+                  body, flags=re.S)
+    body += '\n\\subsection*{Held-out pretraining design rescore}\n'
+    body += ('Saved architecture and gene-panel outputs for the 42 held-out SLE donors were rescored '
+             'separately. On the common 1,006-gene axis, each donor contributed 100 real reference cells, '
+             '100 disjoint real query cells and 100 generated cells per arm. One fixed Poisson read-out, '
+             'a real-reference 50-component PCA and $k=10$ local neighbourhoods defined precision and '
+             'coverage. The architecture and panel families had different training detection floors and '
+             'are not a factorial comparison. One saved generation seed per arm makes these descriptive scores.\n')
+    path.write_text(body)
+
+
+def overlay(final: bool) -> list[str]:
+    changed = []
+    for src in sorted((EDITS / 'sections').glob('*.tex')):
+        dst = STAGE / 'sections' / src.name
+        shutil.copy2(src, dst)
+        changed.append(str(dst.relative_to(STAGE)))
+    edit_method_model()
+    changed.append('sections/methods_model.tex')
+    main = STAGE / 'main.tex'
+    content = main.read_text()
+    content = content.replace('% Overleaf main document.', '% RESTRUCTURING DRAFT: strict Figures 3--5 remain pending.\n% Overleaf main document.', 1)
+    content = content.replace('% Figures with their legends, each on its own page(s). Panels are the deck\'s vector graphics, placed as-is;\n% the 180 mm journal layout is still to be drawn.',
+                              '% Figure 1--5 restructuring draft; strict missing panels are explicitly labelled.')
+    if final:
+        content = content.replace('% RESTRUCTURING DRAFT: strict Figures 3--5 remain pending.\n', '')
+    else:
+        content = content.replace('\\maketitle',
+            '\\maketitle\n\\noindent\\fcolorbox{red}{white}{\\parbox{0.92\\textwidth}{'
+            '\\textbf{RESTRUCTURING DRAFT.} Strict five-pair results for Figs 2--5 '
+            'are incomplete. The approved title, abstract and Introduction retain their '
+            'original wording and must be rereviewed against final strict results.}}\\par\\medskip', 1)
+    main.write_text(content)
+    changed.append('main.tex')
+    supp = STAGE / 'supplementary.tex'
+    supp_text = supp.read_text()
+    supp_text = supp_text.replace('\\begin{document}',
+        '\\begin{document}\n\\noindent\\textcolor{red}{[HISTORICAL SUPPLEMENTARY DRAFT: '
+        'legacy analyses have not been reconciled with exact-five-pair support.]}\\par\\medskip', 1)
+    supp.write_text(supp_text)
+    changed.append('supplementary.tex')
+    figures = dict(FIGURES)
+    if final:
+        complete_results()
+        figures.update(FINAL_FIGURES)
+        strict_figures = {
+            'fig3': ('Healthy exact five-pair OOF', 'fig3_healthy_strict_oof.pdf'),
+            'fig4': ('Disease exact five-pair draws', 'fig4_disease_strict_draws.pdf'),
+            'fig5': ('Paired rare states under exact five-pair support', 'fig5_rare_states_strict.pdf'),
+        }
+        for name, (title, filename) in strict_figures.items():
+            p = STAGE / 'sections' / f'{name}.tex'
+            panels = f'\\figpanelh{{}}{{figures/strict_20261012/{filename}}}{{0.77}}\n'
+            if name == 'fig3':
+                panels += ('\\figpanelh{}{figures/strict_20261012/fig3_realism_metrics.pdf}{0.38}\n')
+                panels += ('\\figpanelh{}{figures/strict_20261012/fig3_canonical_marker_dotplot.pdf}{0.42}\n')
+                for extra in ('umap_by_celltype','composition_fractions','runtime_components'):
+                    panels += f'\\figpanelh{{}}{{figures/strict_20261012/fig3_{extra}.pdf}}{{0.62}}\n'
+            if name == 'fig4':
+                panels += ('\\figpanelh{}{figures/strict_20261012/fig4_disease_signal_strict.pdf}{0.48}\n'
+                           '\\figpanelh{}{figures/strict_20261012/fig4_deconvolution_strict.pdf}{0.42}\n'
+                           '\\figpanelh{}{figures/strict_20261012/fig4_deconvolution_expression_strict.pdf}{0.48}\n')
+                panels += ('\\figpanelh{}{figures/strict_20261012/fig4_historical_5fold_separate.pdf}{0.38}\n')
+                for extra in ('scatter','heatmap','cat'):
+                    panels += f'\\figpanelh{{}}{{figures/strict_20261012/fig4_disease_signal_{extra}.pdf}}{{0.60}}\n'
+            if name == 'fig5':
+                for extra in ('rare_visuals','all_states','behcet_rules'):
+                    panels += f'\\figpanelh{{}}{{figures/strict_20261012/fig5_{extra}_strict.pdf}}{{0.72}}\n'
+            p.write_text(f'\\mainfigure{{fig:{name}}}{{{title}}}\n' + panels +
+                         '\\figlegend{Strict-support results and source-data tables are '
+                         'reported in the corresponding Results section. Figure 4 historical '
+                         'five-fold values appear in a separate labelled panel.}\n')
+    for source, target in figures.items():
+        src = ROOT / 'figures' / source
+        if not src.is_file():
+            raise ValueError(f'missing figure: {src}')
+        dst = STAGE / 'figures/strict_20261012' / target
+        dst.parent.mkdir(parents=True, exist_ok=True)
+        shutil.copy2(src, dst)
+        changed.append(str(dst.relative_to(STAGE)))
+    evidence = ('source_data/fig1_corpus_aggregates.json',
+                'source_data/ablation_pretrain_pc.csv',
+                'source_data/ablation_pretrain_pc_receipt.json',
+                'source_data/fig2_historical_rank_full.csv',
+                'source_data/fig4_historical_5fold.csv',
+                'reports/figure1_provenance.json',
+                'reports/figures234_readiness.json',
+                'reports/rare_provenance.json')
+    if final:
+        evidence += ('source_data/fig2_strict_curve.csv',
+                     'source_data/fig3_per_sample.csv',
+                     'source_data/fig3_extras.csv',
+                     'source_data/fig3_runtime.csv',
+                     'source_data/fig3_runtime.json',
+                     'source_data/fig3_visual_data.json',
+                     'source_data/fig4_strict_per_sample.csv',
+                     'source_data/fig4_corrected_statistics.csv',
+                     'source_data/fig4_cross_draw_donor_ci.csv',
+                     'source_data/fig4_cross_draw_donor_ci.json',
+                     'source_data/fig4_donor_aware_signal.csv',
+                     'source_data/fig4_donor_aware_summary.csv',
+                     'source_data/fig4_donor_aware_genes.csv',
+                     'source_data/fig4_donor_aware_cat.csv',
+                     'source_data/fig4_donor_aware_provenance.json',
+                     'source_data/fig4_strict_contrast.csv',
+                     'source_data/fig4_deconvolution.csv',
+                     'source_data/fig4_deconvolution_signal.csv',
+                     'source_data/rare_summary.csv',
+                     'source_data/rare_ineligible_states.csv',
+                     'source_data/rare_behcet_descriptive.csv')
+    for rel in evidence:
+        src = ROOT / rel
+        if not src.is_file():
+            raise ValueError(f'missing source data: {src}')
+        dst = STAGE / 'strict_20261012' / rel
+        dst.parent.mkdir(parents=True, exist_ok=True)
+        shutil.copy2(src, dst)
+        changed.append(str(dst.relative_to(STAGE)))
+    changed.extend(['sections/fig1.tex', 'sections/fig2.tex', 'sections/fig3.tex',
+                    'sections/fig4.tex', 'sections/fig5.tex'])
+    return sorted(set(changed))
+
+
+def verify_unchanged_frontmatter(original: dict[str, str]) -> None:
+    for name in ('sections/abstract.tex', 'sections/introduction.tex', 'authors.tex'):
+        if digest(STAGE / name) != original[name]:
+            raise ValueError(f'user-approved frontmatter changed: {name}')
+    canonical_main = (CANON / 'main.tex').read_text()
+    staged_main = (STAGE / 'main.tex').read_text()
+    for pattern in (r'\\title\{[^\n]+', r'\\abstract\{[^\n]+'):
+        if re.search(pattern, canonical_main).group() != re.search(pattern, staged_main).group():
+            raise ValueError(f'user-approved title or abstract command changed: {pattern}')
+
+
+def allowed_frontmatter_refresh(previous: dict[str, str], current: dict[str, str],
+                                *, old_main: str | None = None, new_main: str | None = None) -> dict:
+    """Permit only new approved Title, Abstract and Introduction source text."""
+    changed = {name: {'previous_sha256': old, 'current_sha256': current.get(name)}
+               for name, old in previous.items() if current.get(name) != old}
+    allowed = {'main.tex', 'sections/abstract.tex', 'sections/introduction.tex'}
+    extra = set(changed) - allowed
+    if extra:
+        raise ValueError(f'canonical source changed outside approved frontmatter: {sorted(extra)}')
+    if 'main.tex' in changed:
+        if old_main is None or new_main is None:
+            raise ValueError('main.tex changed beyond approved title/abstract commands')
+        pattern = r'\\(?:title|abstract)\{[^\n]*\}'
+        if re.sub(pattern, r'\\frontmatter{APPROVED}', old_main) != re.sub(
+                pattern, r'\\frontmatter{APPROVED}', new_main):
+            raise ValueError('main.tex changed beyond approved title/abstract commands')
+    return changed
+
+
+def main() -> None:
+    p = argparse.ArgumentParser(description=__doc__)
+    mode = p.add_mutually_exclusive_group(required=True)
+    mode.add_argument('--preview', action='store_true')
+    mode.add_argument('--require-complete', action='store_true')
+    args = p.parse_args()
+    if subprocess.check_output(['git', '-C', str(CANON), 'status', '--porcelain']).strip():
+        raise SystemExit('canonical manuscript is not clean; refusing to assemble')
+    checked_provenance(ROOT / 'reports/figure1_provenance.json', 'Figure 1')
+    pretrain = checked_provenance(ROOT / 'source_data/ablation_pretrain_pc_receipt.json', 'Figure 2 P/C')
+    recipe = pretrain.get('recipe', {})
+    if (pretrain.get('schema') != 'pbisc.fig2.pretrain_pc.v1' or
+            recipe.get('n_pcs') != 50 or recipe.get('local_k') != 10 or
+            pretrain.get('gene_axis', {}).get('n') != 1006 or
+            {r['family'] for r in rows(ROOT / 'source_data/ablation_pretrain_pc.csv')} !=
+            {'architecture_floor1pct', 'panel_floor0.1pct'}):
+        raise SystemExit('Figure 2 measured P/C receipt or source table differs from the frozen rescore')
+    gaps, readiness = strict_gate()
+    if args.require_complete and gaps:
+        raise SystemExit('final assembly refused:\n- ' + '\n- '.join(sorted(set(gaps))))
+    previous = STAGE / 'integration_manifest.json'
+    refreshed = {}
+    if previous.is_file() and args.require_complete:
+        prior = document(previous)
+        old = prior.get('canonical_source_sha256', {})
+        current = {rel: digest(CANON / rel) if (CANON / rel).is_file() else None for rel in old}
+        old_main = None
+        if current.get('main.tex') != old.get('main.tex'):
+            old_head = prior.get('canonical_head')
+            if not old_head:
+                raise SystemExit('review preview has no canonical head for frontmatter comparison')
+            old_main = subprocess.check_output(['git', '-C', str(CANON), 'show',
+                                                f'{old_head}:main.tex'], text=True)
+        try:
+            refreshed = allowed_frontmatter_refresh(old, current, old_main=old_main,
+                                                    new_main=(CANON / 'main.tex').read_text())
+        except ValueError as exc:
+            raise SystemExit(str(exc)) from exc
+    originals = copy_source_files()
+    changed = overlay(args.require_complete)
+    verify_unchanged_frontmatter(originals)
+    # Keep the original claims available for review without placing them in Results.
+    legacy = STAGE / 'editorial/legacy_results'
+    legacy.mkdir(parents=True, exist_ok=True)
+    for name in ('results_fig1', 'results_fig2', 'results_fig3', 'results_fig4',
+                 'results_fig5', 'results_fig6', 'methods_paired', 'methods_eval', 'discussion'):
+        src = CANON / 'sections' / f'{name}.tex'
+        shutil.copy2(src, legacy / src.name)
+        changed.append(str((legacy / src.name).relative_to(STAGE)))
+    manifest = {
+        'schema': 'pbisc.paper.manuscript-integration.v1',
+        'mode': 'complete' if args.require_complete else 'restructuring_preview',
+        'canonical_root': str(CANON), 'stage_root': str(STAGE),
+        'canonical_head': subprocess.check_output(['git', '-C', str(CANON), 'rev-parse', 'HEAD'], text=True).strip(),
+        'canonical_source_sha256': originals,
+        'approved_frontmatter_refresh': refreshed,
+        'staged_changes': {rel: {'sha256': digest(STAGE / rel),
+                                 'canonical_sha256': originals.get(rel)} for rel in changed},
+        'figure_source_sha256': {name: digest(ROOT / 'figures' / name) for name in
+                                 (FIGURES | (FINAL_FIGURES if args.require_complete else {}))},
+        'readiness': readiness,
+        'gaps': gaps,
+        'figure6': 'waiting_user_prepared_data; unchanged placeholder',
+        'git_push': False, 'overleaf_sync': False,
+    }
+    previous.write_text(json.dumps(manifest, indent=2) + '\n')
+    print(json.dumps({'mode': manifest['mode'], 'staged_changed_files': len(changed),
+                      'gaps': gaps, 'manifest': str(previous)}, indent=2))
+
+
+if __name__ == '__main__':
+    main()

paper-releases/pbisc-diffusion/updates/20261012T131501Z-strictpairs-final-caption/diffusion/metadata/inference_locations.json

@@ -0,0 +1,5 @@
+{
+  "locations": [],
+  "project_id": "pbisc-diffusion",
+  "update_id": "20261012T131501Z-strictpairs-final-caption"
+}

paper-releases/pbisc-diffusion/updates/20261012T131501Z-strictpairs-final-caption/diffusion/metadata/request.json

@@ -0,0 +1,19 @@
+{
+  "assets": [
+    {
+      "host": "server_1",
+      "kind": "code",
+      "source": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paper_figures_strictpairs_20261012/archive/20261012T131501Z-strictpairs-final-caption/assemble_manuscript.py",
+      "state": "intermediate"
+    },
+    {
+      "host": "server_1",
+      "kind": "code",
+      "source": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paper_figures_strictpairs_20261012/archive/20261012T131501Z-strictpairs-final-caption/assemble_manuscript_before_final_caption_fix.py",
+      "state": "stopped"
+    }
+  ],
+  "inference_locations": [],
+  "project_id": "pbisc-diffusion",
+  "summary": "Final-gated Figure 2 caption fix: remove pending language only after strict completion; include same-readout composition and all comparator budgets, retain original logFC/DEG panels with explicit historical epoch/readout/seed differences. Current review deck/manuscript remain previews. Ten focused checks and syntax compilation passed. No new scientific experiment, GitHub push or Overleaf sync."
+}