Add validated CropMath dataset for private review

.gitattributes

@@ -58,3 +58,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+data/default/test.jsonl filter=lfs diff=lfs merge=lfs -text
+data/eval_prompts/test.jsonl filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -0,0 +1,9 @@
+.venv/
+__pycache__/
+.pytest_cache/
+*.pyc
+.DS_Store
+.env
+.env.*
+*.log
+.cache/

.python-version

@@ -0,0 +1 @@
+3.12

BUILD_INFO.json

@@ -0,0 +1,7 @@
+{
+  "role": "huggingface private review deposit",
+  "dataset_version": "cropmath-v1",
+  "hidden_scoring_service": "unavailable",
+  "visibility": "private",
+  "public_release": false
+}

CITATION.cff

@@ -0,0 +1,25 @@
+cff-version: 1.2.0
+title: 'CropMath: An Objective Benchmark for Mechanistic Formula Reasoning in Agricultural
+  Large Language Models'
+message: If you use this dataset, please cite it using the metadata below.
+type: dataset
+authors:
+- family-names: Ma
+  given-names: Yuanyuan
+  affiliation: Nanjing Agricultural University
+year: 2026
+license: CC-BY-4.0
+abstract: CropMath is an objective benchmark for evaluating mechanistic formula reasoning
+  in agricultural large language models. It contains 62 formulas from 4 public family
+  categories (growth_yield, carbon_nitrogen_cycle, methane_emission, environmental_response),
+  6 knowledge-ablation conditions, and 4 reasoning modes. Ground-truth answers are
+  derived deterministically from the documented mathematical expressions.
+keywords:
+- agricultural science
+- mechanistic formula reasoning
+- formula reasoning
+- numerical reasoning
+- benchmark
+- knowledge ablation
+- LLM evaluation
+repository-code: https://github.com/YuanyuanMa03/CropMath

CODE_LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2026 Agri-Align Contributors
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

HIDDEN_POLICY.md

@@ -0,0 +1,27 @@
+# Answer-withheld auxiliary set
+
+The `default` and `eval_prompts` configurations contain reference answers. The
+`gold` split is a 95-row subset of `test`, not an independent evaluation set.
+
+The `hidden_public` configuration contains 160 additional questions, including
+formula expressions, input parameters and prompts. It does not distribute
+reference answers, solutions or effective-parameter fields. Its sample IDs are
+disjoint from the public development and test splits.
+
+This is a question-public, answer-withheld auxiliary set. Withholding reference
+labels and using disjoint IDs do not establish absence of training contamination:
+the public questions can still be solved and may become part of training data.
+The existing answer commitment fields are retained as metadata; this release
+does not claim that the corresponding private answer files have been located
+and independently checked as part of public-package validation.
+
+No hosted hidden-set scoring service or submission endpoint is included or
+currently offered by this candidate. Public-split scoring can be reproduced
+locally. Hidden-set scoring requires separately verified reference answers and
+a defined evaluation procedure. Any later service must document submission
+format, complete-sample coverage, duplicate and unknown-ID handling, scoring
+rules, access conditions and limits before accepting benchmark submissions.
+
+Private reference answers, private calculators and generation implementations
+are excluded from both publication candidates. This policy does not promise
+future access to those materials.

LICENSE

@@ -0,0 +1 @@
+CropMath dataset release cropmath-v1 is licensed under Creative Commons Attribution 4.0 International (CC BY 4.0): https://creativecommons.org/licenses/by/4.0/

README.md

@@ -0,0 +1,156 @@
+---
+license: cc-by-4.0
+pretty_name: CropMath
+language:
+  - en
+  - zh
+task_categories:
+  - question-answering
+configs:
+  - config_name: default
+    default: true
+    data_files:
+      - split: dev
+        path: data/default/dev.jsonl
+      - split: test
+        path: data/default/test.jsonl
+      - split: gold
+        path: data/default/gold.jsonl
+  - config_name: eval_prompts
+    data_files:
+      - split: dev
+        path: data/eval_prompts/dev.jsonl
+      - split: test
+        path: data/eval_prompts/test.jsonl
+      - split: gold
+        path: data/eval_prompts/gold.jsonl
+  - config_name: hidden_public
+    data_files:
+      - split: hidden_public
+        path: hidden_public/hidden_public.jsonl
+---
+
+# CropMath dataset for private review
+
+CropMath contains agricultural mechanistic formula questions with numeric
+reference answers and controlled knowledge conditions. The `cropmath-v1`
+snapshot is deposited for private review in [myy555/CropMath](https://huggingface.co/datasets/myy555/CropMath).
+The accompanying toolkit is in [YuanyuanMa03/CropMath](https://github.com/YuanyuanMa03/CropMath).
+These repositories require access permission. This is not a public release;
+no DOI or hosted hidden-set evaluation service is provided.
+
+## Contents and split relationships
+
+| Configuration | dev | test | gold | hidden_public |
+|---|---:|---:|---:|---:|
+| default | 252 | 751 | 95 | — |
+| eval_prompts | 1,512 | 4,506 | 570 | — |
+| hidden_public | — | — | — | 160 |
+
+The 95 gold questions are copied from test for auditing; do not add them to the
+test count or treat them as an independent split. There are 1,003 unique
+development/test questions. The six-condition expansion repeats the same
+questions with different knowledge blocks; it does not create independent
+questions. The formula catalog contains 62 public identifiers, CMF001–CMF062.
+
+The public process categories are `growth_yield`, `carbon_nitrogen_cycle`,
+`methane_emission`, and `environmental_response`. Reasoning modes are `direct`,
+`sensitivity`, `branch`, and `chain_2`.
+
+## Local loading
+
+Run this example from the dataset directory with the `datasets` package installed:
+
+```python
+from pathlib import Path
+from datasets import load_dataset
+
+path = str(Path.cwd())
+questions = load_dataset(path, "default")
+prompts = load_dataset(path, "eval_prompts")
+auxiliary = load_dataset(path, "hidden_public")
+assert len(questions["test"]) == 751
+assert len(prompts["test"]) == 4506
+assert len(auxiliary["hidden_public"]) == 160
+```
+
+The standalone Hugging Face candidate also contains `pyproject.toml`, `uv.lock`,
+validation scripts and dataset tests. From its root:
+
+```bash
+uv sync --locked
+uv run --locked pytest -q tests
+uv run --locked python scripts/validate_cropmath_release.py --release-dir . --no-scan-repo-root
+uv run --locked python scripts/validate_formula_catalog.py --path metadata/formula_catalog.csv
+```
+
+For the copy inside the GitHub candidate, use that repository's root README
+commands instead. Validation success means the specified local checks passed;
+it does not establish scientific validity or online Viewer behavior.
+
+## Authenticated remote loading
+
+For an account granted access to the private dataset, authenticate with
+`hf auth login` in an environment containing the Hugging Face CLI, then run:
+
+```python
+from datasets import load_dataset
+
+questions = load_dataset("myy555/CropMath", "default", token=True)
+prompts = load_dataset("myy555/CropMath", "eval_prompts", token=True)
+auxiliary = load_dataset("myy555/CropMath", "hidden_public", token=True)
+```
+
+The local loading instructions remain useful for downloaded copies. Do not
+publish access tokens or include them in notebooks and scripts.
+
+## Fields and use
+
+`default` rows include `id`, `problem`, `formula`, `parameters`, reasoning mode,
+knowledge blocks, per-condition prompts, `answer` and `solution`.
+`eval_prompts` rows include a condition-specific `id`, the original `sample_id`,
+`condition`, `prompt`, `answer_float`, `precision` and grouping metadata.
+Only send the selected `prompt` to a model. Do not include the answer, solution,
+other conditions' knowledge blocks or scoring metadata in the model input.
+
+The six conditions are C (formula and inputs), K_name (name), K_formula
+(parameter semantics), K_domain (domain context), K_distractor (distractors),
+and K_wrong (an incorrect formula). The target remains the reference answer
+to the original task even when K_wrong supplies an incorrect formula.
+
+Numeric scoring uses:
+
+```text
+abs(prediction - answer) <= max(0.5 * 10**(-precision), abs(answer) * 0.01)
+```
+
+Unparseable predictions count as incorrect. Preserve sample pairing across
+conditions and account for formula-level clustering in statistical inference.
+See `eval.yaml` for the serialized protocol and `HIDDEN_POLICY.md` for auxiliary-set access.
+
+## Provenance and limitations
+
+The snapshot contains standardized expressions, reference labels, a public
+formula catalog and audit metadata. It does not distribute private calculator
+implementations, generation code or a complete per-formula bibliographic mapping.
+Consequently, this package supports reusing questions and checking numeric
+predictions against stored labels, but does not independently reproduce the
+entire formula acquisition and reference-answer generation process.
+
+The audit CSV and protocols are supplied records, not a new independent human
+audit performed by the package validator. Automated parser tests check the
+serialized solutions; they do not certify the human-audit provenance.
+Inputs are synthetic, and this benchmark does not establish reliability on
+field observations, complete crop simulations or real agricultural decisions.
+
+The 160 auxiliary questions are public while their answers are withheld. No
+hosted scoring service is supplied. ID disjointness and withheld labels are not
+proof of absence of training contamination. See `HIDDEN_POLICY.md`.
+
+## Licensing and attribution
+
+Dataset contents are provided under CC BY 4.0; see `LICENSE`. Validation code
+included in the standalone candidate uses the MIT terms in `CODE_LICENSE`.
+The GitHub candidate has a separate MIT license for its code. Attribution
+metadata is provided in `CITATION.cff`, including the private toolkit address.
+No DOI or public release identifier is asserted. Existing notices are preserved.

data/default/test.jsonl

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+oid sha256:1443ba77d490a7a697adf1fdd83e2e46e8222423970266f987087dd45a3bc554
+size 12942947

data/eval_prompts/test.jsonl

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+oid sha256:008444e4e01946fd545082b4a348eaed067cce5198e21bad4a8ec49cd18984e4
+size 11262714

eval.yaml

@@ -0,0 +1,44 @@
+# CropMath v1 evaluation protocol.
+#
+# This file is a framework-neutral protocol description.
+
+name: CropMath
+version: cropmath-v1
+primary_config: eval_prompts
+primary_split: test
+hidden_config: hidden_public
+hidden_policy: answers_not_distributed
+hidden_scoring_service: unavailable
+conditions:
+  - C
+  - K_name
+  - K_formula
+  - K_domain
+  - K_distractor
+  - K_wrong
+prompt_field: prompt
+target_field: answer_float
+metadata_fields:
+  - sample_id
+  - formula_id
+  - family
+  - mode
+  - level
+  - precision
+decoding:
+  temperature: 0.0
+  max_new_tokens: 2048
+  seed: 42
+  thinking_mode: off
+answer_extraction_order:
+  - boxed
+  - gsm8k_hashes
+  - explicit_answer_line
+  - last_number_fallback
+correctness:
+  type: numeric_tolerance
+  expression: abs(prediction - answer_float) <= max(0.5 * 10^-precision, abs(answer_float) * 0.01)
+statistics:
+  paired_test: mcnemar_exact
+  effect_size: paired_accuracy_delta
+  multiple_testing: benjamini_hochberg_fdr

hidden_public/hidden_policy.json

@@ -0,0 +1,27 @@
+{
+  "hidden_samples": 160,
+  "seed": 20260609,
+  "public_file": "release/cropmath-v1/hidden_public/hidden_public.jsonl",
+  "private_answer_file": "not_included_in_public_release",
+  "answer_release_policy": "question-public, answer-withheld auxiliary set; formulas, inputs and prompts are public; no hosted scoring service; disjoint IDs do not prove absence of training contamination",
+  "families": {
+    "carbon_nitrogen_cycle": 35,
+    "methane_emission": 27,
+    "growth_yield": 76,
+    "environmental_response": 22
+  },
+  "modes": {
+    "branch": 21,
+    "chain_2": 21,
+    "direct": 57,
+    "sensitivity": 61
+  },
+  "levels": {
+    "1": 28,
+    "2": 58,
+    "3": 40,
+    "4": 34
+  },
+  "public_id_overlap": 0,
+  "private_answer_verification": "not verified by this public candidate build"
+}

metadata/category_summary.csv

@@ -0,0 +1,229 @@
+split,category,value,count
+dev,family,carbon_nitrogen_cycle,65
+dev,family,methane_emission,47
+dev,family,growth_yield,111
+dev,family,environmental_response,29
+dev,subject,carbon-nitrogen cycling nitrogen,5
+dev,subject,carbon-nitrogen cycling photosynthesis,24
+dev,subject,carbon-nitrogen cycling respiration,8
+dev,subject,carbon-nitrogen cycling soil carbon,12
+dev,subject,carbon-nitrogen cycling stress,4
+dev,subject,carbon-nitrogen cycling water,7
+dev,subject,Dry matter partitioning,17
+dev,subject,Leaf area growth,13
+dev,subject,Methane,47
+dev,subject,Nitrogen,5
+dev,subject,Phenology,26
+dev,subject,Photosynthesis,22
+dev,subject,Respiration,19
+dev,subject,environmental-response formula system,29
+dev,subject,Temperature response,4
+dev,subject,Temperature stress,9
+dev,subject,Yield formation,1
+dev,mode,branch,33
+dev,mode,chain_2,33
+dev,mode,direct,100
+dev,mode,sensitivity,86
+dev,math_type,Beta temperature response,8
+dev,math_type,Biomass-weighted allocation,1
+dev,math_type,Chained multiplicative decomposition,4
+dev,math_type,Chained sum,4
+dev,math_type,Double logistic,2
+dev,math_type,Exponential growth,2
+dev,math_type,Exponential quadratic,7
+dev,math_type,Exponential ratio,4
+dev,math_type,Linear,12
+dev,math_type,Linear decline,4
+dev,math_type,Logarithmic,11
+dev,math_type,Logarithmic minimum,3
+dev,math_type,Logistic,2
+dev,math_type,Maximum linear,8
+dev,math_type,Maximum with chained drivers,6
+dev,math_type,Michaelis-Menten response,4
+dev,math_type,Minimum stress multiplier,3
+dev,math_type,Multi-step sigmoid,3
+dev,math_type,Multiplicative,8
+dev,math_type,Multiplicative conversion,10
+dev,math_type,Multiplicative minimum stress,3
+dev,math_type,Multiplicative with minimum stress,6
+dev,math_type,Piecewise exponential,6
+dev,math_type,Piecewise exponential decay,6
+dev,math_type,Piecewise linear,4
+dev,math_type,Piecewise linear cap,4
+dev,math_type,Piecewise linear stress,5
+dev,math_type,Piecewise linear/exponential,1
+dev,math_type,Piecewise logistic,3
+dev,math_type,Piecewise minimum,4
+dev,math_type,Piecewise polynomial,4
+dev,math_type,Piecewise power penalty,6
+dev,math_type,Piecewise quadratic,2
+dev,math_type,Piecewise trigonometric,4
+dev,math_type,Piecewise water response,7
+dev,math_type,Power attenuation,2
+dev,math_type,Power product,2
+dev,math_type,Power response,5
+dev,math_type,Product,14
+dev,math_type,Product with Q10 temperature response,4
+dev,math_type,Product with exponential saturation,2
+dev,math_type,Q10 temperature response,4
+dev,math_type,Q10 with DVI correction,8
+dev,math_type,Q10 with temperature clipping,5
+dev,math_type,Quadratic polynomial,2
+dev,math_type,Ratio,7
+dev,math_type,Residual from shoot partitioning,6
+dev,math_type,Residual with piecewise components,3
+dev,math_type,Stage-dependent product,12
+dev,math_type,Subtraction and conversion,5
+dev,level,1,57
+dev,level,2,93
+dev,level,3,54
+dev,level,4,48
+gold,family,carbon_nitrogen_cycle,20
+gold,family,methane_emission,15
+gold,family,growth_yield,49
+gold,family,environmental_response,11
+gold,subject,carbon-nitrogen cycling nitrogen,2
+gold,subject,carbon-nitrogen cycling photosynthesis,8
+gold,subject,carbon-nitrogen cycling respiration,2
+gold,subject,carbon-nitrogen cycling soil carbon,5
+gold,subject,carbon-nitrogen cycling water,1
+gold,subject,Dry matter partitioning,12
+gold,subject,Leaf area growth,10
+gold,subject,Methane,15
+gold,subject,Nitrogen,2
+gold,subject,Phenology,8
+gold,subject,Photosynthesis,9
+gold,subject,Respiration,5
+gold,subject,environmental-response formula system,11
+gold,subject,Temperature stress,4
+gold,subject,Yield formation,1
+gold,mode,branch,12
+gold,mode,chain_2,15
+gold,mode,direct,35
+gold,mode,sensitivity,33
+gold,math_type,Beta temperature response,1
+gold,math_type,Biomass-weighted allocation,1
+gold,math_type,Chained multiplicative decomposition,1
+gold,math_type,Chained sum,1
+gold,math_type,Exponential growth,4
+gold,math_type,Exponential ratio,1
+gold,math_type,Exponential saturation,1
+gold,math_type,Linear,2
+gold,math_type,Logarithmic,4
+gold,math_type,Logarithmic minimum,3
+gold,math_type,Logistic,1
+gold,math_type,Maximum linear,2
+gold,math_type,Michaelis-Menten response,3
+gold,math_type,Minimum stress multiplier,3
+gold,math_type,Multi-step sigmoid,5
+gold,math_type,Multiplicative,3
+gold,math_type,Multiplicative conversion,2
+gold,math_type,Multiplicative with minimum stress,2
+gold,math_type,Piecewise exponential,5
+gold,math_type,Piecewise exponential decay,2
+gold,math_type,Piecewise linear,4
+gold,math_type,Piecewise linear cap,3
+gold,math_type,Piecewise linear stress,1
+gold,math_type,Piecewise linear/exponential,3
+gold,math_type,Piecewise logistic,2
+gold,math_type,Piecewise minimum,1
+gold,math_type,Piecewise polynomial,2
+gold,math_type,Piecewise power penalty,2
+gold,math_type,Piecewise quadratic,5
+gold,math_type,Piecewise water response,1
+gold,math_type,Power attenuation,2
+gold,math_type,Power response,2
+gold,math_type,Product,3
+gold,math_type,Product with Q10 temperature response,2
+gold,math_type,Product with exponential saturation,1
+gold,math_type,Q10 temperature response,1
+gold,math_type,Q10 with DVI correction,2
+gold,math_type,Q10 with temperature clipping,2
+gold,math_type,Quadratic polynomial,3
+gold,math_type,Ratio,2
+gold,math_type,Residual with piecewise components,1
+gold,math_type,Subtraction and conversion,3
+gold,level,1,20
+gold,level,2,34
+gold,level,3,26
+gold,level,4,15
+test,family,carbon_nitrogen_cycle,168
+test,family,methane_emission,127
+test,family,growth_yield,353
+test,family,environmental_response,103
+test,subject,carbon-nitrogen cycling nitrogen,31
+test,subject,carbon-nitrogen cycling photosynthesis,42
+test,subject,carbon-nitrogen cycling respiration,10
+test,subject,carbon-nitrogen cycling soil carbon,53
+test,subject,carbon-nitrogen cycling stress,14
+test,subject,carbon-nitrogen cycling water,11
+test,subject,Dry matter partitioning,79
+test,subject,Leaf area growth,53
+test,subject,Methane,127
+test,subject,Nitrogen,7
+test,subject,Phenology,68
+test,subject,Photosynthesis,62
+test,subject,Respiration,40
+test,subject,environmental-response formula system,103
+test,subject,Temperature response,14
+test,subject,Temperature stress,27
+test,subject,Yield formation,10
+test,mode,branch,99
+test,mode,chain_2,99
+test,mode,direct,272
+test,mode,sensitivity,281
+test,math_type,Beta temperature response,27
+test,math_type,Biomass-weighted allocation,11
+test,math_type,Chained multiplicative decomposition,14
+test,math_type,Chained sum,14
+test,math_type,Double logistic,16
+test,math_type,Exponential growth,16
+test,math_type,Exponential quadratic,5
+test,math_type,Exponential ratio,14
+test,math_type,Exponential saturation,12
+test,math_type,Linear,23
+test,math_type,Linear decline,8
+test,math_type,Logarithmic,13
+test,math_type,Logarithmic minimum,15
+test,math_type,Logistic,10
+test,math_type,Maximum linear,22
+test,math_type,Maximum with chained drivers,12
+test,math_type,Michaelis-Menten response,14
+test,math_type,Minimum stress multiplier,15
+test,math_type,Multi-step sigmoid,15
+test,math_type,Multiplicative,28
+test,math_type,Multiplicative conversion,8
+test,math_type,Multiplicative minimum stress,15
+test,math_type,Multiplicative with minimum stress,12
+test,math_type,Piecewise exponential,30
+test,math_type,Piecewise exponential decay,12
+test,math_type,Piecewise linear,14
+test,math_type,Piecewise linear cap,14
+test,math_type,Piecewise linear stress,13
+test,math_type,Piecewise linear/exponential,17
+test,math_type,Piecewise logistic,15
+test,math_type,Piecewise minimum,20
+test,math_type,Piecewise polynomial,14
+test,math_type,Piecewise power penalty,12
+test,math_type,Piecewise quadratic,22
+test,math_type,Piecewise trigonometric,14
+test,math_type,Piecewise water response,11
+test,math_type,Power attenuation,10
+test,math_type,Power product,10
+test,math_type,Power response,13
+test,math_type,Product,32
+test,math_type,Product with Q10 temperature response,14
+test,math_type,Product with exponential saturation,10
+test,math_type,Q10 temperature response,13
+test,math_type,Q10 with DVI correction,10
+test,math_type,Q10 with temperature clipping,13
+test,math_type,Quadratic polynomial,10
+test,math_type,Ratio,17
+test,math_type,Residual from shoot partitioning,12
+test,math_type,Residual with piecewise components,15
+test,math_type,Stage-dependent product,12
+test,math_type,Subtraction and conversion,13
+test,level,1,153
+test,level,2,270
+test,level,3,190
+test,level,4,138

metadata/dataset_stats.json

@@ -0,0 +1,128 @@
+{
+  "data_version": "cropmath-v1",
+  "source_data_dir": "release/cropmath-v1[private path removed]",
+  "official_unique_samples": 1003,
+  "dev_test_overlap": 0,
+  "gold_subset_of_test": true,
+  "conditions": [
+    "C",
+    "K_name",
+    "K_formula",
+    "K_domain",
+    "K_distractor",
+    "K_wrong"
+  ],
+  "splits": {
+    "dev": {
+      "rows": 252,
+      "unique_ids": 252,
+      "formulas": 61,
+      "families": {
+        "carbon_nitrogen_cycle": 65,
+        "methane_emission": 47,
+        "growth_yield": 111,
+        "environmental_response": 29
+      },
+      "modes": {
+        "branch": 33,
+        "chain_2": 33,
+        "direct": 100,
+        "sensitivity": 86
+      },
+      "levels": {
+        "1": 57,
+        "2": 93,
+        "3": 54,
+        "4": 48
+      }
+    },
+    "test": {
+      "rows": 751,
+      "unique_ids": 751,
+      "formulas": 62,
+      "families": {
+        "carbon_nitrogen_cycle": 168,
+        "methane_emission": 127,
+        "growth_yield": 353,
+        "environmental_response": 103
+      },
+      "modes": {
+        "branch": 99,
+        "chain_2": 99,
+        "direct": 272,
+        "sensitivity": 281
+      },
+      "levels": {
+        "1": 153,
+        "2": 270,
+        "3": 190,
+        "4": 138
+      }
+    },
+    "gold": {
+      "rows": 95,
+      "unique_ids": 95,
+      "formulas": 48,
+      "families": {
+        "carbon_nitrogen_cycle": 20,
+        "methane_emission": 15,
+        "growth_yield": 49,
+        "environmental_response": 11
+      },
+      "modes": {
+        "branch": 12,
+        "chain_2": 15,
+        "direct": 35,
+        "sensitivity": 33
+      },
+      "levels": {
+        "1": 20,
+        "2": 34,
+        "3": 26,
+        "4": 15
+      }
+    },
+    "hidden_public": {
+      "rows": 160,
+      "unique_ids": 160,
+      "formulas": 56,
+      "families": {
+        "carbon_nitrogen_cycle": 35,
+        "methane_emission": 27,
+        "growth_yield": 76,
+        "environmental_response": 22
+      },
+      "modes": {
+        "branch": 21,
+        "chain_2": 21,
+        "direct": 57,
+        "sensitivity": 61
+      },
+      "levels": {
+        "1": 28,
+        "2": 58,
+        "3": 40,
+        "4": 34
+      }
+    }
+  },
+  "eval_prompt_rows": {
+    "dev": 1512,
+    "test": 4506,
+    "gold": 570
+  },
+  "hidden_public_rows": 160,
+  "skipped_rows": {
+    "dev": [],
+    "test": [
+      "CMF051_sensitivity_t1_0001",
+      "CMF046_sensitivity_t0_0001",
+      "CMF054_sensitivity_t0_0000",
+      "CMF011_sensitivity_t1_0000",
+      "CMF028_sensitivity_t0_0000"
+    ],
+    "gold": [
+      "CMF051_sensitivity_t1_0001"
+    ]
+  }
+}

metadata/dataset_tables.md

@@ -0,0 +1,8 @@
+### Split Counts
+
+| Split | Rows | Unique IDs | Formulas |
+|---|---:|---:|---:|
+| dev | 252 | 252 | 61 |
+| test | 751 | 751 | 62 |
+| gold | 95 | 95 | 48 |
+| hidden_public | 160 | 160 | 56 |

metadata/error_taxonomy_protocol.md

@@ -0,0 +1,16 @@
+# CropMath Error Taxonomy Protocol
+
+Annotate at least 200 incorrect core-model predictions sampled across model, condition, family, and mode.
+
+Allowed primary/secondary error types:
+
+- `formula_selection_error`
+- `parameter_substitution_error`
+- `arithmetic_computation_error`
+- `branch_condition_error`
+- `sensitivity_change_handling_error`
+- `unit_precision_rounding_error`
+- `final_answer_extraction_format_error`
+- `hallucinated_or_ignored_formula`
+
+Set `parser_extraction_correct` to `yes`, `no`, or `unclear` after comparing the raw response with the parsed prediction.

metadata/error_taxonomy_template.csv

@@ -0,0 +1 @@
+annotation_id,model_tag,condition,sample_id,formula_id,family,mode,level,ground_truth,prediction,primary_error_type,secondary_error_type,parser_extraction_correct,human_notes

metadata/evaluation_manifest.json

@@ -0,0 +1,31 @@
+{
+  "name": "CropMath v1 formal evaluation manifest",
+  "data_version": "cropmath-v1",
+  "official_unique_samples": 1003,
+  "test_samples": 751,
+  "gold_policy": "gold is a 95-sample audit subset copied from test, not an independent split",
+  "hidden_policy": "question-public, answer-withheld auxiliary set; formulas, inputs and prompts are public; no hosted scoring service; disjoint IDs do not prove absence of training contamination",
+  "conditions": [
+    "C",
+    "K_name",
+    "K_formula",
+    "K_domain",
+    "K_distractor",
+    "K_wrong"
+  ],
+  "prompt_config": "eval_prompts",
+  "prompt_field": "prompt",
+  "decoding": {
+    "temperature": 0.0,
+    "max_new_tokens": 2048,
+    "seed": 42
+  },
+  "correctness": {
+    "rule": "abs(prediction - ground_truth) <= max(0.5*10^-precision, abs(ground_truth)*0.01)"
+  },
+  "statistics": {
+    "paired_test": "McNemar exact test at item level",
+    "effect_size": "paired accuracy delta",
+    "multiple_testing": "Benjamini-Hochberg FDR"
+  }
+}

metadata/formula_catalog.csv

@@ -0,0 +1,63 @@
+formula_id,family,primary_subject,name_en,name_zh,unit,precision,expression,latex,math_type,math_types,modes,sample_count
+CMF001,carbon_nitrogen_cycle,carbon-nitrogen cycling photosynthesis,carbon-nitrogen cycling CO2 fertilization factor,作物二氧化碳施肥因子,multiplier,3,1 + Coef_B_CO2 * ln(CO2 / 340),F_{CO2}=1+B\ln(CO2/340),Logarithmic,Logarithmic,direct;sensitivity,14
+CMF002,carbon_nitrogen_cycle,carbon-nitrogen cycling photosynthesis,carbon-nitrogen cycling gross primary production,总初级生产力,g C/m2/day,3,Photo_Rate_opt * F_T * F_Water * F_CO2 * Day_Length_hour * 0.0432,GPP=P_{opt}F_TF_WF_{CO2}DL\cdot0.0432,Multiplicative conversion,Multiplicative conversion,sensitivity;direct;chain_2,20
+CMF003,carbon_nitrogen_cycle,Nitrogen,Nitrogen use efficiency,氮利用效率,kg grain/kg N,2,GrainYield / NUptake,NUE=\frac{GrainYield}{NUptake},Ratio,Ratio,direct;sensitivity,14
+CMF004,carbon_nitrogen_cycle,carbon-nitrogen cycling nitrogen,carbon-nitrogen cycling crop nitrogen demand,作物需氮量,g N/m2/day,3,"if NPP<0: 0; if N_shoot<3.5 and DVI<0.3: Coef_Plant_TN_uptake*N_shoot; else: min(N_requirement_max_day, Ratio_N_C_photo_product*NPP)","N_d=C_uN_{shoot}\;\text{or}\;\min(N_{max},r_NNPP)",Piecewise minimum,Piecewise minimum,chain_2;direct;branch;sensitivity,25
+CMF005,carbon_nitrogen_cycle,carbon-nitrogen cycling nitrogen,carbon-nitrogen cycling shoot nitrogen allocation,地上部氮分配量,g N/m2,3,Plant_TN_uptake * Biom_shoot / (Biom_shoot + Biom_root),N_{shoot}=N_{uptake}\frac{B_{shoot}}{B_{shoot}+B_{root}},Biomass-weighted allocation,Biomass-weighted allocation,sensitivity;direct,13
+CMF006,carbon_nitrogen_cycle,carbon-nitrogen cycling photosynthesis,carbon-nitrogen cycling canopy absorbed PAR,冠层吸收光合有效辐射,umol/m2/s,2,Radi * 0.44 * 4.6 * (1-Coef_rou) * (1-exp(-Coef_K*LAI)) / (Coef_K*LAI),PAR=Radi\cdot0.44\cdot4.6(1-\rho)\frac{1-e^{-KLAI}}{KLAI},Exponential ratio,Exponential ratio,direct;chain_2;sensitivity,19
+CMF007,carbon_nitrogen_cycle,carbon-nitrogen cycling photosynthesis,carbon-nitrogen cycling optimal photosynthetic rate,最适光合速率,umol CO2/m2/s,3,(Coef_alfa * Leaf_N) * PAR / (PAR + Coef_beta),P_{opt}=\alpha N_{leaf}\frac{PAR}{PAR+\beta},Michaelis-Menten response,Michaelis-Menten response,sensitivity;chain_2;direct,21
+CMF008,carbon_nitrogen_cycle,carbon-nitrogen cycling respiration,carbon-nitrogen cycling plant maintenance respiration,植株维持呼吸,g C/m2/day,3,0.0432*24*(Biom_plant_yesterday/0.45)*Coef_Rm*2^((Tmn-25)/10) / (if DVI>1: DVI^2; else: 1),R_m=0.0432\cdot24(Biom/0.45)C_m2^{(T-25)/10},Q10 with DVI correction,Q10 with DVI correction,branch;direct;sensitivity,20
+CMF009,carbon_nitrogen_cycle,carbon-nitrogen cycling soil carbon,carbon-nitrogen cycling carbon pool respiration loss,碳库呼吸损失,g C/m2/day,3,Pool*Coef_K_Decom*F_temp*F_water*F_texture*F_pH*F_notill*(1-Coef_K_Trans),R=PoolK F_TF_WF_{texture}F_{pH}F_{notill}(1-K_{trans}),Chained multiplicative decomposition,Chained multiplicative decomposition,direct;sensitivity;chain_2,19
+CMF010,carbon_nitrogen_cycle,carbon-nitrogen cycling soil carbon,carbon-nitrogen cycling soil pH decomposition factor,土壤pH分解因子,fraction,3,1 / (1 + exp(2.5 * (5 - pH))),F_{pH}=\frac{1}{1+e^{2.5(5-pH)}},Logistic,Logistic,direct;sensitivity,13
+CMF011,carbon_nitrogen_cycle,carbon-nitrogen cycling soil carbon,carbon-nitrogen cycling soil carbon temperature factor,土壤碳分解温度因子,multiplier,3,if is_soil_temp>=0.5: 2.4**((Temp-10)*0.1); else: 2.4**((4.4+0.76*Temp-10)*0.1),F_T=2.4^{(T_{soil}-10)/10}\;\text{where}\;T_{soil}=T\;\text{or}\;4.4+0.76T,Q10 temperature response,Q10 temperature response,sensitivity;direct;branch,18
+CMF012,carbon_nitrogen_cycle,carbon-nitrogen cycling soil carbon,carbon-nitrogen cycling soil carbon water factor,土壤碳分解水分因子,fraction,3,if Soil_Water>=Saturate_Water: 0.65; else: 0.49*exp(3.88*(Soil_Water/BD)-5.4*(Soil_Water/BD)^2),F_W=0.49e^{3.88W-5.4W^2},Piecewise exponential,Piecewise exponential,sensitivity;branch;direct,20
+CMF013,carbon_nitrogen_cycle,carbon-nitrogen cycling stress,carbon-nitrogen cycling crop temperature activity factor,作物温度活性因子,response factor,3,if Td<=Tmin_active or Td>=Tmax_active: 0; else: ((Td-Tmin_active)/(Topt_active-Tmin_active))^(1+Coef_T_M) * ((Tmax_active-Td)/(Tmax_active-Topt_active))^(1-Coef_T_M),F_T=\left(\frac{T_d-T_{min}}{T_{opt}-T_{min}}\right)^{1+M}\left(\frac{T_{max}-T_d}{T_{max}-T_{opt}}\right)^{1-M},Beta temperature response,Beta temperature response,direct;branch;sensitivity,18
+CMF014,carbon_nitrogen_cycle,carbon-nitrogen cycling water,carbon-nitrogen cycling crop water stress factor,作物水分胁迫因子,fraction,3,if Soil_Water<=Wilt_point: 0; if Soil_Water<Crop_Water_min: (Soil_Water-Wilt_point)/(Crop_Water_min-Wilt_point); if Soil_Water<Crop_Water_max: 1; else: 0.5*(1+(1-Soil_Water)/(1-Crop_Water_max)),"F_W=f(\theta,\theta_{wp},\theta_{min},\theta_{max})",Piecewise water response,Piecewise water response,sensitivity;branch;direct,19
+CMF015,methane_emission,Methane,Root-exudate carbon substrate,根系分泌碳底物,g C/m2/day,3,0.0018 * VI * SI * W ** 1.25,C_r=0.0018VI\cdot SI\cdot W^{1.25},Power product,Power product,direct;sensitivity,12
+CMF016,methane_emission,Methane,Methane ebullition emission,甲烷冒泡排放,g CH4/m2/day,3,"min(0.7 * ln(t_soil) / Wr, 0.9) * P","E_{bl}=\min(0.7\ln(t_{soil})/W_r,0.9)P",Logarithmic minimum,Logarithmic minimum,chain_2;sensitivity;direct,21
+CMF017,methane_emission,Methane,Total methane emission,甲烷总排放,g CH4/m2/day,3,Ebl + P * CH4RiceEfC * (1 - W/Wmax)^0.25,E=E_{bl}+P\cdot C(1-W/W_{max})^{0.25},Chained sum,Chained sum,chain_2;sensitivity;direct,19
+CMF018,methane_emission,Methane,Redox potential factor,氧化还原电位因子,fraction,3,if Eh<-150: 1; else: exp(-1.7*(1+Eh/150)),"F_{Eh}=1\;(Eh<-150),\quad e^{-1.7(1+Eh/150)}",Piecewise exponential,Piecewise exponential,direct;sensitivity;branch,21
+CMF019,methane_emission,Methane,Plant methane transport factor,植株传输因子,fraction,3,CH4RiceEfC * (1 - W / Wmax) ** 0.25,F_p=C(1-W/W_{max})^{0.25},Power attenuation,Power attenuation,sensitivity;direct,14
+CMF020,methane_emission,Methane,Fresh organic matter carbon decomposition,新鲜有机质碳分解量,g C/m2/day,3,WI * SI * TI * 0.027 * OMN,OMNC=WI\cdot SI\cdot TI\cdot0.027\cdot OMN,Multiplicative,Multiplicative,direct;sensitivity;chain_2,20
+CMF021,methane_emission,Methane,Soil organic matter carbon decomposition,土壤有机质碳分解量,g C/m2/day,3,WI * SI * TI * 0.003 * OMS,OMSC=WI\cdot SI\cdot TI\cdot0.003\cdot OMS,Multiplicative,Multiplicative,chain_2;sensitivity;direct,19
+CMF022,methane_emission,Methane,Methane production,甲烷产生量,g CH4/m2/day,3,"max(0, 0.27 * FEh * (TI * Cr + Com))","P=\max(0,0.27F_{Eh}(TI\cdot C_r+Com))",Maximum with chained drivers,Maximum with chained drivers,chain_2;sensitivity;direct,18
+CMF023,methane_emission,Methane,Methane temperature index,甲烷温度指数,multiplier,3,"Q10^((min(t_soil,30)-30)/10)",TI=Q_{10}^{(t_{sl}-30)/10},Q10 with temperature clipping,Q10 with temperature clipping,sensitivity;direct;branch,20
+CMF024,methane_emission,Methane,Soil temperature from air temperature,土壤温度估算,C,2,4.4 + 0.76 * Tair,T_{soil}=4.4+0.76T_{air},Linear,Linear,direct;sensitivity,13
+CMF025,methane_emission,Methane,Water-content decomposition factor,水分分解因子,fraction,3,0.49 * exp(3.88 * WaterC - 5.4 * WaterC^2),WI=0.49e^{3.88W_c-5.4W_c^2},Exponential quadratic,Exponential quadratic,sensitivity;direct,12
+CMF026,growth_yield,Photosynthesis,Actual maximum assimilation rate,实际最大同化速率,kg CO2/ha/h,2,"Am * FCO2 * FPA * FT * min(NNI, WDF)","AMAX=Am\cdot F_{CO2}\cdot F_{PA}\cdot F_T\cdot\min(NNI,WDF)",Multiplicative with minimum stress,Multiplicative with minimum stress,sensitivity;direct;chain_2,20
+CMF027,growth_yield,Phenology,Daily physiological effectiveness,每日生理效应,physiological days/day,3,if PDT<8: DTE*IE; if PDT<18: DTE*RPE; if PDT<32: DTE; if PDT<57: DTE*BFF; else: 0,"DPE=DTE\cdot IE,\;DTE\cdot RPE,\;DTE,\;DTE\cdot BFF",Stage-dependent product,Stage-dependent product,chain_2;sensitivity;branch;direct,24
+CMF028,growth_yield,Phenology,Emergence thermal requirement,出苗热量需求,C day,1,45 + 7 * SDEPTH,EMGDD=45+7SDEPTH,Linear,Linear,direct;sensitivity,11
+CMF029,growth_yield,Photosynthesis,CO2 response factor,二氧化碳影响因子,multiplier,2,1 + beta * ln(Cx / 340),F_{CO2}=1+\beta\ln(C_x/340),Logarithmic,Logarithmic,direct;sensitivity,14
+CMF030,growth_yield,Photosynthesis,Physiological age factor,生理年龄因子,fraction,2,if PDT<28: 1; else: exp(-a*(PDT-28)),"F_{PA}=1\;(PDT<28),\quad e^{-a(PDT-28)}\;(PDT\ge 28)",Piecewise exponential decay,Piecewise exponential decay,direct;branch;sensitivity,20
+CMF031,growth_yield,Photosynthesis,Light interception fraction,光能截获率,fraction,2,1 - exp(-k * LAI),fPAR = 1 - e^{-k \cdot LAI},Exponential saturation,Exponential saturation,direct;sensitivity,13
+CMF032,growth_yield,Temperature response,Temperature response factor,温度响应因子,fraction,2,if Tb<=T<Tol: sin(pi/2*(T-Tb)/(Tol-Tb)); if Tol<=T<Tou: 1; if Tou<=T<Tmax: cos(pi/2*(T-Tou)/(Tmax-Tou)); else: 0,F_T=\sin(\frac{T-T_b}{T_{ol}-T_b}\frac{\pi}{2}); 1; \cos(\frac{T-T_{ou}}{T_{max}-T_{ou}}\frac{\pi}{2}),Piecewise trigonometric,Piecewise trigonometric,direct;branch;sensitivity,18
+CMF033,growth_yield,Respiration,Daily dry matter increment,日干物质增量,kg/ha/day,2,(DTGA - RM - RG) / (1 - b),GCR=\frac{DTGA-RM-RG}{1-b},Subtraction and conversion,Subtraction and conversion,chain_2;sensitivity;direct,21
+CMF034,growth_yield,Dry matter partitioning,Harvest index,收获指数,fraction,2,Y_grain / B_above,HI=\frac{Y_{grain}}{B_{above}},Ratio,Ratio,direct;sensitivity,12
+CMF035,growth_yield,Temperature stress,High-temperature fertility factor,高温结实因子,fraction,2,if 32<=PDT<=39 and Tmax_day>36.6: 1/(1+exp(0.853*(Tmax_day-36.6))); else: 1,HTF=\frac{1}{1+e^{0.853(T_m-36.6)}},Piecewise logistic,Piecewise logistic,sensitivity;branch;direct,20
+CMF036,growth_yield,Photosynthesis,Canopy extinction coefficient,��层消光系数,dimensionless,3,0.0087 * PDT + 0.2222,K=0.0087PDT+0.2222,Linear,Linear,sensitivity;direct,13
+CMF037,growth_yield,Leaf area growth,Potential leaf area index,潜在叶面积指数,m2/m2,2,LAI0 * exp(RP * GDD),LAI_P=LAI_0e^{RP\cdot GDD},Exponential growth,Exponential growth,sensitivity;chain_2;direct,22
+CMF038,growth_yield,Leaf area growth,Leaf area index from SLA,比叶面积法叶面积指数,m2/m2,2,SLA * AWL,LAI=SLA\cdot AWL,Product,Product,direct;sensitivity,13
+CMF039,growth_yield,Temperature stress,Low-temperature fertility factor,低温结实因子,fraction,2,if 26<=PDT<=39 and Tmean<22: 1-(4.6+0.054*Qt^1.56)/100; else: 1,LTF=1-\frac{4.6+0.054Q_t^{1.56}}{100},Piecewise power penalty,Piecewise power penalty,branch;sensitivity;direct,20
+CMF040,growth_yield,Phenology,Critical daylength,临界日长,h,2,Po + sqrt(1 / PS),P_c=P_o+\sqrt{1/PS},Power response,Power response,direct;sensitivity;chain_2,20
+CMF041,growth_yield,Dry matter partitioning,Green leaf partitioning index,绿叶分配指数,fraction,2,if PDT<26: 0.54-0.0046*PDT; else: 1.4532*exp(-0.0492*PDT),"PIGL=0.54-0.0046PDT\;(PDT<26),\quad1.4532e^{-0.0492PDT}\;(PDT\ge26)",Piecewise linear/exponential,Piecewise linear/exponential,sensitivity;direct;branch,21
+CMF042,growth_yield,Dry matter partitioning,Panicle partitioning index,穗分配指数,fraction,2,(Y_grain / B_above / 0.87) / (1 + exp(-0.2804 * (PDT - 39))),PIP=\frac{HI/0.87}{1+e^{-0.2804(PDT-39)}},Multi-step sigmoid,Multi-step sigmoid,direct;branch;sensitivity,23
+CMF043,growth_yield,Dry matter partitioning,Root partitioning index,地下部分配指数,fraction,2,1 - (-0.0000842*PDT^2 + 0.01*PDT + 0.63),PIRO=1-PISH,Residual from shoot partitioning,Residual from shoot partitioning,chain_2;sensitivity;direct,18
+CMF044,growth_yield,Dry matter partitioning,Shoot partitioning index,地上部分配指数,fraction,2,-0.0000842 * PDT^2 + 0.01 * PDT + 0.63,PISH=-8.42\times10^{-5}PDT^2+0.01PDT+0.63,Quadratic polynomial,Quadratic polynomial,sensitivity;direct,15
+CMF045,growth_yield,Dry matter partitioning,Stem partitioning index,茎鞘分配指数,fraction,2,1 - (if PDT<26: 0.54-0.0046*PDT; else: 1.4532*exp(-0.0492*PDT)) - (Y_grain/B_above/0.87)/(1+exp(-0.2804*(PDT-39))),PIS=1-PIGL-PIP,Residual with piecewise components,Residual with piecewise components,chain_2;sensitivity;direct,19
+CMF046,growth_yield,Respiration,Growth respiration,生长呼吸,kg/ha/day,2,Rg * DTGA,RG=R_g\cdot DTGA,Product,Product,direct;sensitivity,11
+CMF047,growth_yield,Photosynthesis,Intercepted photosynthetically active radiation,截获光合有效辐射,MJ/m2/day,2,PAR * (1 - exp(-k * LAI)),IPAR = PAR \cdot (1 - e^{-k \cdot LAI}),Product with exponential saturation,Product with exponential saturation,direct;sensitivity,13
+CMF048,growth_yield,Respiration,Maintenance respiration,维持呼吸,kg/ha/day,2,(0.0091 - 0.0001 * PDT) * ABIOMASS * Q10**((T-To)/10),RM=(0.0091-0.0001\cdot PDT)\cdot ABIOMASS\cdot Q_{10}^{(T-T_o)/10},Product with Q10 temperature response,Product with Q10 temperature response,chain_2;direct;sensitivity,20
+CMF049,growth_yield,Respiration,Maintenance respiration coefficient at optimum temperature,最适温度维持呼吸系数,d-1,4,0.0091 - 0.0001 * PDT,RM(T_o)=0.0091-0.0001PDT,Linear decline,Linear decline,direct;sensitivity,12
+CMF050,growth_yield,Phenology,Relative photoperiod effectiveness,相对光周期效应,fraction,2,if P<=Po: 1; if P<=Po+sqrt(1/PS): 1-PS*(P-Po)^2; else: 0,"RPE=1,\;1-PS(P-P_o)^2,\;0",Piecewise quadratic,Piecewise quadratic,sensitivity;branch;direct;chain_2,29
+CMF051,growth_yield,Phenology,Relative thermal effectiveness,相对热效应,fraction,3,(((T - Tb)/(To - Tb)) * (((Tm - T)/(Tm - To)) ** ((Tm - To)/(To - Tb)))) ** TS,RTE=\left[\frac{T-T_b}{T_o-T_b}\left(\frac{T_m-T}{T_m-T_o}\right)^{(T_m-T_o)/(T_o-T_b)}\right]^{TS},Beta temperature response,Beta temperature response,direct;branch;sensitivity,18
+CMF052,growth_yield,Leaf area growth,Actual LAI relative growth rate,实际叶面积相对增长率,d-1,4,"RP * min(NNI, WDF)","R=RP\cdot\min(NNI,WDF)",Minimum stress multiplier,Minimum stress multiplier,chain_2;sensitivity;direct,21
+CMF053,growth_yield,Leaf area growth,Specific leaf area,比叶面积,cm2/g,2,if GDD<=1200: (-0.0002*GDD^2-0.5604*GDD+581.04)*(SLAc/200); else: 200*(SLAc/200),SLA=(-0.0002GDD^2-0.5604GDD+581.04)(SLA_c/200),Piecewise polynomial,Piecewise polynomial,direct;sensitivity;branch,20
+CMF054,growth_yield,Yield formation,Dry grain yield,稻谷干重产量,kg/ha,1,AWSP * grain_fraction,Y=AWSP\cdot f_{grain},Product,Product,sensitivity;direct,12
+CMF055,environmental_response,environmental-response formula system,environmental-response daily biomass increment,环境响应日生物量增量,kg/ha/day,2,"10 * RUE * fSolar * SRAD * F_CO2 * F_Temp * min(F_Water, F_Heat)","dB=10RUEfSolarSRADF_{CO2}F_T\min(F_W,F_H)",Multiplicative minimum stress,Multiplicative minimum stress,direct;sensitivity;chain_2,18
+CMF056,environmental_response,environmental-response formula system,environmental-response daily thermal time,每日有效积温,C day,2,"max(Tmean - Tbase, 0)","dTT=\max(T_{mean}-T_{base},0)",Maximum linear,Maximum linear,branch;direct;sensitivity,18
+CMF057,environmental_response,environmental-response formula system,environmental-response CO2 response,环境响应二氧化碳响应,multiplier,3,"if CO2>=700: 1+CO2_RUE*350/100; else: max(CO2_RUE*CO2*0.01+1-0.01*350*CO2_RUE, 1)","F_{CO2}=f(CO2,CO2_{RUE})",Piecewise linear cap,Piecewise linear cap,branch;direct;sensitivity,21
+CMF058,environmental_response,environmental-response formula system,environmental-response heat stress response,环境响应高温响应,fraction,3,"if Tmax<=MaxT: 1; if Tmax>ExtremeT: 0; else: max(1-(Tmax-MaxT)/(ExtremeT-MaxT), 0)","F_H=1,\;0,\;\text{or}\;1-\frac{T_{max}-MaxT}{ExtremeT-MaxT}",Piecewise linear stress,Piecewise linear stress,branch;sensitivity;direct,19
+CMF059,environmental_response,environmental-response formula system,environmental-response solar interception fraction,环境响应光截获比例,fraction,3,"min(fSolarMax/(1+exp(-0.01*(TT-I50A))), fSolarMax/(1+exp(0.01*(TT-(Tsum-I50B))))) * min(fSolar_water, 1)","fSolar=\min(f_1,f_2)F_{solar,water}",Double logistic,Double logistic,chain_2;direct;sensitivity,18
+CMF060,environmental_response,environmental-response formula system,environmental-response temperature response,环境响应温度响应,fraction,3,"if Tmean>=Topt: 1; else: max((Tmean-Tbase)/(Topt-Tbase), 0)","F_T=1\;\text{or}\;\max((T-T_b)/(T_o-T_b),0)",Piecewise linear,Piecewise linear,direct;branch;sensitivity,22
+CMF061,environmental_response,environmental-response formula system,environmental-response water stress response,环境响应水分响应,response factor,3,"max(0, 1 - S_Water * ARID)","F_W=\max(0,1-S_WARID)",Maximum linear,Maximum linear,sensitivity;direct,14
+CMF062,environmental_response,environmental-response formula system,environmental-response yield,环境响应产量,kg/ha,1,Biomass * HI,Yield=Biomass\cdot HI,Product,Product,direct;sensitivity,13

metadata/gold_audit.csv

@@ -0,0 +1,96 @@
+id,formula_id,family,mode,level,template_id,answer,problem_sha256_16,automated_validation,in_test_split,human_problem_clear,human_formula_match,human_answer_verified,human_notes
+CMF060_direct_t2_0001,CMF060,environmental_response,direct,2,2,0.613,042fccc52dae33de,pass,yes,yes,yes,yes,
+CMF016_sensitivity_t0_0001,CMF016,methane_emission,sensitivity,2,0,0.021,b6a26e68802a9dee,pass,yes,yes,yes,yes,
+CMF010_direct_t2_0001,CMF010,carbon_nitrogen_cycle,direct,1,2,0.938,0cb999a965ac93c9,pass,yes,yes,yes,yes,
+CMF048_chain_2_t0_0001,CMF048,growth_yield,chain_2,4,0,40.55,867a19a09fb7f2b8,pass,yes,yes,yes,yes,
+CMF058_branch_t0_0001,CMF058,environmental_response,branch,4,0,0.506,38612559d8c0ad9c,pass,yes,yes,yes,yes,
+CMF011_sensitivity_t0_0000,CMF011,carbon_nitrogen_cycle,sensitivity,3,0,2.380,f423fe2d4b8d1405,pass,yes,yes,yes,yes,
+CMF003_direct_t1_0000,CMF003,carbon_nitrogen_cycle,direct,1,1,69.61,c4486b08d6759bc1,pass,yes,yes,yes,yes,
+CMF012_sensitivity_t1_0001,CMF012,carbon_nitrogen_cycle,sensitivity,3,1,0.974,2a98c683c8d4cc40,pass,yes,yes,yes,yes,
+CMF018_direct_t0_0001,CMF018,methane_emission,direct,2,0,0.104,e5e3b76cf76badaa,pass,yes,yes,yes,yes,
+CMF054_sensitivity_t2_0000,CMF054,growth_yield,sensitivity,2,2,4925.7,ea2149445581a94f,pass,yes,yes,yes,yes,
+CMF052_sensitivity_t0_0000,CMF052,growth_yield,sensitivity,2,0,0.0027,04f5a1b04334a3c3,pass,yes,yes,yes,yes,
+CMF023_sensitivity_t1_0001,CMF023,methane_emission,sensitivity,2,1,0.314,f1f1421436664b56,pass,yes,yes,yes,yes,
+CMF050_branch_t1_0001,CMF050,growth_yield,branch,4,1,0.74,3ec425c9fb690b6e,pass,yes,yes,yes,yes,
+CMF023_direct_t0_0000,CMF023,methane_emission,direct,1,0,0.313,bc88f40f3f9dac50,pass,yes,yes,yes,yes,
+CMF002_sensitivity_t1_0000,CMF002,carbon_nitrogen_cycle,sensitivity,3,1,34.785,04a7d02b4fcd6f9b,pass,yes,yes,yes,yes,
+CMF044_sensitivity_t0_0000,CMF044,growth_yield,sensitivity,2,0,0.91,7d3f58c6dda0e553,pass,yes,yes,yes,yes,
+CMF001_direct_t0_0000,CMF001,carbon_nitrogen_cycle,direct,1,0,1.078,f388c1ca3d4db55d,pass,yes,yes,yes,yes,
+CMF045_chain_2_t1_0000,CMF045,growth_yield,chain_2,4,1,0.62,1f30c4a0c0277ca0,pass,yes,yes,yes,yes,
+CMF016_chain_2_t0_0000,CMF016,methane_emission,chain_2,3,0,0.009,ee7391d9e146dbd5,pass,yes,yes,yes,yes,
+CMF019_sensitivity_t0_0000,CMF019,methane_emission,sensitivity,2,0,0.343,49a67ea264b6554f,pass,yes,yes,yes,yes,
+CMF026_sensitivity_t0_0000,CMF026,growth_yield,sensitivity,3,0,19.42,c11a9590ff5f0ec6,pass,yes,yes,yes,yes,
+CMF012_branch_t1_0000,CMF012,carbon_nitrogen_cycle,branch,4,1,0.739,0b6b0e604333259b,pass,yes,yes,yes,yes,
+CMF003_direct_t2_0001,CMF003,carbon_nitrogen_cycle,direct,1,2,47.09,a838147a4d004049,pass,yes,yes,yes,yes,
+CMF039_branch_t0_0001,CMF039,growth_yield,branch,4,0,0.91,c711cb5db2a6dfcd,pass,yes,yes,yes,yes,
+CMF031_direct_t2_0001,CMF031,growth_yield,direct,1,2,0.98,8d28250ffa45930d,pass,yes,yes,yes,yes,
+CMF020_direct_t2_0001,CMF020,methane_emission,direct,1,2,3.441,48e5ba64c737f53d,pass,yes,yes,yes,yes,
+CMF017_chain_2_t1_0001,CMF017,methane_emission,chain_2,4,1,5.200,4c6bd0e3c0fab26a,pass,yes,yes,yes,yes,
+CMF052_chain_2_t2_0000,CMF052,growth_yield,chain_2,3,2,0.0061,4c1a8130d0562f37,pass,yes,yes,yes,yes,
+CMF037_sensitivity_t1_0001,CMF037,growth_yield,sensitivity,2,1,1.40,83c8affe4d6e0818,pass,yes,yes,yes,yes,
+CMF042_branch_t2_0000,CMF042,growth_yield,branch,3,2,0.49,10c9285187e129b4,pass,yes,yes,yes,yes,
+CMF018_direct_t0_0000,CMF018,methane_emission,direct,2,0,0.074,660bdd10bc097a24,pass,yes,yes,yes,yes,
+CMF041_sensitivity_t2_0001,CMF041,growth_yield,sensitivity,3,2,0.14,4ef148d088524aa7,pass,yes,yes,yes,yes,
+CMF002_direct_t1_0000,CMF002,carbon_nitrogen_cycle,direct,2,1,22.903,a45408f5d38137bf,pass,yes,yes,yes,yes,
+CMF052_chain_2_t1_0001,CMF052,growth_yield,chain_2,3,1,0.0035,8950d5ae9f62a04a,pass,yes,yes,yes,yes,
+CMF057_branch_t0_0001,CMF057,environmental_response,branch,4,0,1.630,32a8dfc1ddc519ad,pass,yes,yes,yes,yes,
+CMF004_chain_2_t1_0001,CMF004,carbon_nitrogen_cycle,chain_2,4,1,0.656,6198e3249a68839c,pass,yes,yes,yes,yes,
+CMF030_direct_t2_0001,CMF030,growth_yield,direct,2,2,1.00,f7ee48991f0ff85c,pass,yes,yes,yes,yes,
+CMF062_direct_t2_0001,CMF062,environmental_response,direct,1,2,4924.7,9d508478a7ca783d,pass,yes,yes,yes,yes,
+CMF006_direct_t2_0001,CMF006,carbon_nitrogen_cycle,direct,1,2,442.59,a33b74972afc04ae,pass,yes,yes,yes,yes,
+CMF036_sensitivity_t1_0000,CMF036,growth_yield,sensitivity,2,1,0.493,e62f90beb8dcce48,pass,yes,yes,yes,yes,
+CMF050_sensitivity_t0_0000,CMF050,growth_yield,sensitivity,3,0,0.00,7b22c1e9de84c965,pass,yes,yes,yes,yes,
+CMF029_direct_t0_0001,CMF029,growth_yield,direct,1,0,1.43,480b63057226921c,pass,yes,yes,yes,yes,
+CMF035_sensitivity_t0_0001,CMF035,growth_yield,sensitivity,3,0,0.01,c90f81f31de3ccb8,pass,yes,yes,yes,yes,
+CMF018_sensitivity_t0_0001,CMF018,methane_emission,sensitivity,3,0,1.000,105779388b7911d7,pass,yes,yes,yes,yes,
+CMF037_chain_2_t2_0001,CMF037,growth_yield,chain_2,3,2,8.87,81ab37cc9e23ebee,pass,yes,yes,yes,yes,
+CMF042_branch_t2_0001,CMF042,growth_yield,branch,3,2,0.33,2d54dc5eb01d09d5,pass,yes,yes,yes,yes,
+CMF035_sensitivity_t0_0000,CMF035,growth_yield,sensitivity,3,0,1.00,2ea50795d618f845,pass,yes,yes,yes,yes,
+CMF005_sensitivity_t0_0000,CMF005,carbon_nitrogen_cycle,sensitivity,2,0,4.368,1458ac1794deee52,pass,yes,yes,yes,yes,
+CMF007_chain_2_t2_0001,CMF007,carbon_nitrogen_cycle,chain_2,3,2,46.309,1b3f48ffb376e00c,pass,yes,yes,yes,yes,
+CMF057_direct_t0_0000,CMF057,environmental_response,direct,2,0,1.406,eacf7365bef49f36,pass,yes,yes,yes,yes,
+CMF050_direct_t1_0000,CMF050,growth_yield,direct,2,1,0.40,dcc3edb8dafb8edf,pass,yes,yes,yes,yes,
+CMF053_direct_t1_0001,CMF053,growth_yield,direct,2,1,154.75,885c95c8ef3d46b7,pass,yes,yes,yes,yes,
+CMF061_sensitivity_t2_0000,CMF061,environmental_response,sensitivity,2,2,0.412,1f8d7d01630cc692,pass,yes,yes,yes,yes,
+CMF039_branch_t0_0000,CMF039,growth_yield,branch,4,0,0.90,112989edea36ddb1,pass,yes,yes,yes,yes,
+CMF030_direct_t2_0000,CMF030,growth_yield,direct,2,2,1.00,502aba5b87e148fc,pass,yes,yes,yes,yes,
+CMF008_branch_t2_0000,CMF008,carbon_nitrogen_cycle,branch,4,2,1.232,4612208c534fd0cf,pass,yes,yes,yes,yes,
+CMF050_sensitivity_t1_0001,CMF050,growth_yield,sensitivity,3,1,1.00,0a8a33de8cfe8224,pass,yes,yes,yes,yes,
+CMF060_direct_t0_0001,CMF060,environmental_response,direct,2,0,0.820,b70ba4ba6565d647,pass,yes,yes,yes,yes,
+CMF047_direct_t2_0000,CMF047,growth_yield,direct,1,2,13.47,8e68e601080d0c50,pass,yes,yes,yes,yes,
+CMF042_direct_t2_0000,CMF042,growth_yield,direct,1,2,0.28,04947236d53903fe,pass,yes,yes,yes,yes,
+CMF040_direct_t2_0001,CMF040,growth_yield,direct,1,2,13.06,b077e03f04cfeaf5,pass,yes,yes,yes,yes,
+CMF053_sensitivity_t1_0000,CMF053,growth_yield,sensitivity,3,1,270.36,210b5d1f725e7409,pass,yes,yes,yes,yes,
+CMF016_chain_2_t1_0001,CMF016,methane_emission,chain_2,3,1,0.006,82177b021af2d85e,pass,yes,yes,yes,yes,
+CMF037_sensitivity_t0_0001,CMF037,growth_yield,sensitivity,2,0,0.27,f24ed277f1ee7a73,pass,yes,yes,yes,yes,
+CMF019_sensitivity_t2_0001,CMF019,methane_emission,sensitivity,2,2,0.206,625f4d9f61a70e81,pass,yes,yes,yes,yes,
+CMF041_direct_t2_0001,CMF041,growth_yield,direct,2,2,0.15,7fded1def9fd2cf5,pass,yes,yes,yes,yes,
+CMF007_sensitivity_t0_0000,CMF007,carbon_nitrogen_cycle,sensitivity,2,0,43.148,7bdcdf9aa14215fb,pass,yes,yes,yes,yes,
+CMF026_sensitivity_t1_0001,CMF026,growth_yield,sensitivity,3,1,7.96,d9a1b05e88737c49,pass,yes,yes,yes,yes,
+CMF040_sensitivity_t2_0000,CMF040,growth_yield,sensitivity,2,2,12.20,af95d6c8fa909b85,pass,yes,yes,yes,yes,
+CMF042_direct_t2_0001,CMF042,growth_yield,direct,1,2,0.41,b3c7b6d3113d0ea4,pass,yes,yes,yes,yes,
+CMF001_direct_t2_0000,CMF001,carbon_nitrogen_cycle,direct,1,2,1.327,b951ef4d27238d15,pass,yes,yes,yes,yes,
+CMF042_direct_t0_0000,CMF042,growth_yield,direct,1,0,0.01,abfac17ee627e860,pass,yes,yes,yes,yes,
+CMF041_branch_t0_0001,CMF041,growth_yield,branch,4,0,0.26,5bb0fdfb0d0b32d6,pass,yes,yes,yes,yes,
+CMF037_chain_2_t0_0000,CMF037,growth_yield,chain_2,3,0,1.21,6257e00b71f55a00,pass,yes,yes,yes,yes,
+CMF033_chain_2_t0_0001,CMF033,growth_yield,chain_2,3,0,410.21,d8d1742a83e07d31,pass,yes,yes,yes,yes,
+CMF014_sensitivity_t1_0001,CMF014,carbon_nitrogen_cycle,sensitivity,3,1,1.000,0e83526d175904d1,pass,yes,yes,yes,yes,
+CMF033_sensitivity_t1_0001,CMF033,growth_yield,sensitivity,2,1,475.26,7effb0c14d2bec8d,pass,yes,yes,yes,yes,
+CMF038_direct_t2_0001,CMF038,growth_yield,direct,1,2,0.69,6394c484b339997f,pass,yes,yes,yes,yes,
+CMF057_branch_t2_0000,CMF057,environmental_response,branch,4,2,1.413,9dd0190c9dcddb6c,pass,yes,yes,yes,yes,
+CMF021_chain_2_t1_0001,CMF021,methane_emission,chain_2,3,1,1.376,d47610ee48dde0d9,pass,yes,yes,yes,yes,
+CMF044_direct_t0_0000,CMF044,growth_yield,direct,1,0,0.70,32f25bbf4f3fcbff,pass,yes,yes,yes,yes,
+CMF024_direct_t1_0001,CMF024,methane_emission,direct,1,1,28.04,985a92fc82f35fc0,pass,yes,yes,yes,yes,
+CMF033_chain_2_t1_0000,CMF033,growth_yield,chain_2,3,1,295.16,71b2f8f7b9c66f8f,pass,yes,yes,yes,yes,
+CMF050_chain_2_t2_0000,CMF050,growth_yield,chain_2,4,2,0.18,249fb22041bf889f,pass,yes,yes,yes,yes,
+CMF060_branch_t1_0001,CMF060,environmental_response,branch,4,1,0.624,236913273dc976d2,pass,yes,yes,yes,yes,
+CMF009_direct_t2_0000,CMF009,carbon_nitrogen_cycle,direct,2,2,1.100,5a57b3c9db3c56b2,pass,yes,yes,yes,yes,
+CMF029_sensitivity_t1_0001,CMF029,growth_yield,sensitivity,2,1,1.37,07c4adbed2bb15d3,pass,yes,yes,yes,yes,
+CMF044_sensitivity_t1_0001,CMF044,growth_yield,sensitivity,2,1,0.86,a9a4ef8c41f5ef63,pass,yes,yes,yes,yes,
+CMF008_direct_t0_0001,CMF008,carbon_nitrogen_cycle,direct,2,0,2.995,1560a9668a47e0b0,pass,yes,yes,yes,yes,
+CMF007_sensitivity_t2_0001,CMF007,carbon_nitrogen_cycle,sensitivity,2,2,28.928,8c5d64d6dedf0672,pass,yes,yes,yes,yes,
+CMF020_direct_t1_0001,CMF020,methane_emission,direct,1,1,1.354,e2d266c85b37544a,pass,yes,yes,yes,yes,
+CMF051_direct_t1_0001,CMF051,growth_yield,direct,2,1,0.358,93bf508277f54f44,pass,yes,yes,yes,yes,
+CMF048_direct_t1_0000,CMF048,growth_yield,direct,2,1,14.91,7cd30d1aab937777,pass,yes,yes,yes,yes,
+CMF060_sensitivity_t0_0001,CMF060,environmental_response,sensitivity,3,0,0.000,9ff0ef1139350686,pass,yes,yes,yes,yes,
+CMF061_sensitivity_t0_0000,CMF061,environmental_response,sensitivity,2,0,0.425,d711c174969422f5,pass,yes,yes,yes,yes,

metadata/gold_audit_protocol.md

@@ -0,0 +1,12 @@
+# CropMath v1 Gold Audit Protocol
+
+The gold file is a 95-row audit worksheet copied from the frozen test split. It
+is not an independent evaluation split.
+
+For each row, verify that the problem is clear, the formula matches the intended
+quantity and mode, and the serialized answer recomputes from the effective
+parameters within the formula precision. Use `yes`, `no`, or `unclear` in the
+human audit columns and record issues in `human_notes`.
+
+If any row fails, fix the generator/calculator and rebuild the release. Do not
+patch individual JSONL rows by hand.

metadata/hidden_policy.json

@@ -0,0 +1,27 @@
+{
+  "hidden_samples": 160,
+  "seed": 20260609,
+  "public_file": "release/cropmath-v1/hidden_public/hidden_public.jsonl",
+  "private_answer_file": "not_included_in_public_release",
+  "answer_release_policy": "question-public, answer-withheld auxiliary set; formulas, inputs and prompts are public; no hosted scoring service; disjoint IDs do not prove absence of training contamination",
+  "families": {
+    "carbon_nitrogen_cycle": 35,
+    "methane_emission": 27,
+    "growth_yield": 76,
+    "environmental_response": 22
+  },
+  "modes": {
+    "branch": 21,
+    "chain_2": 21,
+    "direct": 57,
+    "sensitivity": 61
+  },
+  "levels": {
+    "1": 28,
+    "2": 58,
+    "3": 40,
+    "4": 34
+  },
+  "public_id_overlap": 0,
+  "private_answer_verification": "not verified by this public candidate build"
+}

pyproject.toml

@@ -0,0 +1,16 @@
+[project]
+name = "cropmath-public-candidate"
+version = "0.0.0"
+description = "Local validation environment for the CropMath public candidate"
+requires-python = ">=3.12,<3.13"
+dependencies = ["datasets==5.0.1"]
+
+[dependency-groups]
+dev = ["pytest==9.1.1"]
+
+[tool.uv]
+package = false
+
+[tool.pytest.ini_options]
+testpaths = ["tests"]
+pythonpath = ["src", "."]

scripts/validate_cropmath_release.py

@@ -0,0 +1,251 @@
+#!/usr/bin/env python3
+"""Validate the CropMath Hugging Face release package."""
+
+from __future__ import annotations
+
+import argparse
+import json
+from pathlib import Path
+import re
+
+
+EXPECTED = {
+    "default": {"dev": 252, "test": 751, "gold": 95},
+    "eval_prompts": {"dev": 1512, "test": 4506, "gold": 570},
+}
+EXPECTED_HIDDEN_PUBLIC = 160
+CONDITIONS = {"C", "K_name", "K_formula", "K_domain", "K_distractor", "K_wrong"}
+PUBLIC_CONTENT_SUFFIXES = {".json", ".jsonl", ".csv", ".yaml", ".yml"}
+FORBIDDEN_PUBLIC_CONTENT = {
+    "specific framework name": re.compile(
+        r"RiceGrow|CH4MOD|AgroC|\bSIMPLE\b|\bDSSAT\b|\bAPSIM\b|"
+        r"\bWOFOST\b|\bORYZA\b|\bDNDC\b|\bCENTURY\b|\bDayCent\b|"
+        r"\bCERES\b|\bAquaCrop\b|\bSTICS\b|\bEPIC\b"
+    ),
+    "source-code wording": re.compile(
+        r"source[ -]?code|codebase|源代码|源码|代码溯源|代码实现|代码位置",
+        re.IGNORECASE,
+    ),
+    "implementation file reference": re.compile(
+        r"(?:^|[\s'\"])(?:src|scripts)/[^\s'\"]+|\b[^\s/]+\.(?:py|R)\b",
+        re.IGNORECASE,
+    ),
+    "generated citation": re.compile(
+        r"\bet\s+al\.?\b|\bdoi\s*:|https?://|\bcited in\b|\bcitation\b",
+        re.IGNORECASE,
+    ),
+}
+
+# Code-area scan: catches model-name and provenance leaks in the public repo's
+# Python/Markdown sources. Unlike FORBIDDEN_PUBLIC_CONTENT this does NOT reject
+# legitimate ``.py`` references (code files legitimately live in the repo) and
+# does NOT reject generic URLs (eval scripts reference model hubs); it focuses
+# on the specific residue that would reveal the private formula provenance.
+REPO_ROOT_SCAN_DIRS = ("src", "evaluation", "scripts", "tests")
+REPO_ROOT_SCAN_FILES = ("README.md", "AGENTS.md")
+REPO_ROOT_CODE_SUFFIXES = {".py", ".md", ".yaml", ".yml", ".sh"}
+REPO_ROOT_FORBIDDEN = {
+    "specific framework name": re.compile(
+        r"RiceGrow|CH4MOD|AgroC|\bSIMPLE crop\b|\bSIMPLE model\b|"
+        r"\bDSSAT\b|\bAPSIM\b|\bWOFOST\b|\bORYZA\b|\bDNDC\b|"
+        r"\bCENTURY\b|\bDayCent\b|\bCERES\b|\bAquaCrop\b|\bSTICS\b|\bEPIC\b"
+    ),
+    "provenance citation in code": re.compile(
+        r"\b(?:Tang|Huang|Herbst|Zhao)\s+(?:19|20)\d{2}\b|"
+        r"\bfrom\s+(?:CH4MOD|RiceGrow|AgroC)\s+code\b|"
+        r"\bCommon\.R\b|\bfunc_[A-Za-z][A-Za-z0-9_]+",
+        re.IGNORECASE,
+    ),
+    "implementation file reference": re.compile(
+        r"\bcropmath\.formulas\b|\bcropmath\.generator\b|"
+        r"\b[^\s/]+\.R\b",
+        re.IGNORECASE,
+    ),
+}
+# Files that legitimately encode the forbidden patterns as a *defense* (the
+# validator itself and the clean-release builder, both of which carry the
+# blocklist). Scanned but whitelisted by relative path so the defense keeps
+# working without false positives.
+REPO_ROOT_SCAN_ALLOWLIST = {
+    "scripts/validate_cropmath_release.py",
+    "scripts/build_clean_public_release.py",
+}
+
+
+def load_jsonl(path: Path) -> list[dict]:
+    with path.open(encoding="utf-8") as f:
+        return [json.loads(line) for line in f if line.strip()]
+
+
+def require(condition: bool, message: str, issues: list[str]) -> None:
+    if not condition:
+        issues.append(message)
+
+
+def validate_public_content(release_dir: Path) -> list[str]:
+    """Reject private implementation and citation residue in public data files."""
+    issues: list[str] = []
+    for path in sorted(release_dir.rglob("*")):
+        if not path.is_file() or path.suffix.lower() not in PUBLIC_CONTENT_SUFFIXES:
+            continue
+        text = path.read_text(encoding="utf-8", errors="replace")
+        for label, pattern in FORBIDDEN_PUBLIC_CONTENT.items():
+            match = pattern.search(text)
+            if match:
+                relative = path.relative_to(release_dir)
+                issues.append(f"{relative}: {label}: {match.group(0)!r}")
+    return issues
+
+
+def validate_repo_root_content(repo_root: Path) -> list[str]:
+    """Reject private provenance residue in the public repo's own source files.
+
+    Scans ``src/``, ``evaluation/``, ``scripts/``, ``tests/`` plus top-level
+    markdown for crop-model names, paper-year citations, and implementation
+    references that would reveal the private formula provenance. The validator
+    itself is allowlisted so its defensive blocklist keeps working.
+    """
+    issues: list[str] = []
+    candidates: list[Path] = []
+    for name in REPO_ROOT_SCAN_DIRS:
+        directory = repo_root / name
+        if directory.is_dir():
+            for path in directory.rglob("*"):
+                if path.is_file() and path.suffix.lower() in REPO_ROOT_CODE_SUFFIXES:
+                    candidates.append(path)
+    for name in REPO_ROOT_SCAN_FILES:
+        path = repo_root / name
+        if path.is_file():
+            candidates.append(path)
+    for path in sorted(candidates):
+        try:
+            relative = path.relative_to(repo_root).as_posix()
+        except ValueError:
+            relative = str(path)
+        if relative in REPO_ROOT_SCAN_ALLOWLIST:
+            continue
+        text = path.read_text(encoding="utf-8", errors="replace")
+        for label, pattern in REPO_ROOT_FORBIDDEN.items():
+            match = pattern.search(text)
+            if match:
+                issues.append(f"{relative}: {label}: {match.group(0)!r}")
+    return issues
+
+
+def validate_jsonl(release_dir: Path) -> list[str]:
+    issues: list[str] = []
+    rows: dict[tuple[str, str], list[dict]] = {}
+    for config, split_counts in EXPECTED.items():
+        for split, expected_n in split_counts.items():
+            path = release_dir / "data" / config / f"{split}.jsonl"
+            require(path.exists(), f"missing file: {path}", issues)
+            if not path.exists():
+                continue
+            data = load_jsonl(path)
+            rows[(config, split)] = data
+            ids = [row["id"] for row in data]
+            require(len(data) == expected_n, f"{config}/{split}: {len(data)} rows, expected {expected_n}", issues)
+            require(len(ids) == len(set(ids)), f"{config}/{split}: duplicate IDs", issues)
+            require(all(row.get("answer") not in (None, "") for row in data), f"{config}/{split}: missing answer", issues)
+            if config == "eval_prompts":
+                require(all(row.get("prompt") for row in data), f"{config}/{split}: missing prompt", issues)
+                require({row.get("condition") for row in data} <= CONDITIONS, f"{config}/{split}: invalid condition", issues)
+
+    dev_ids = {row["id"] for row in rows.get(("default", "dev"), [])}
+    test_ids = {row["id"] for row in rows.get(("default", "test"), [])}
+    gold_ids = {row["id"] for row in rows.get(("default", "gold"), [])}
+    require(not (dev_ids & test_ids), "default/dev and default/test overlap", issues)
+    require(gold_ids <= test_ids, "default/gold is not a subset of default/test", issues)
+
+    for split in ["dev", "test", "gold"]:
+        default_ids = {row["id"] for row in rows.get(("default", split), [])}
+        eval_rows = rows.get(("eval_prompts", split), [])
+        eval_sample_ids = [row["sample_id"] for row in eval_rows]
+        require(set(eval_sample_ids) == default_ids, f"eval_prompts/{split}: sample IDs do not match default/{split}", issues)
+        for sample_id in default_ids:
+            sample_conditions = {row["condition"] for row in eval_rows if row["sample_id"] == sample_id}
+            require(sample_conditions == CONDITIONS, f"eval_prompts/{split}: {sample_id} does not have all six conditions", issues)
+
+    hidden_path = release_dir / "hidden_public" / "hidden_public.jsonl"
+    require(hidden_path.exists(), "missing hidden public file", issues)
+    if hidden_path.exists():
+        hidden_rows = load_jsonl(hidden_path)
+        hidden_ids = {row["id"] for row in hidden_rows}
+        require(len(hidden_rows) == EXPECTED_HIDDEN_PUBLIC, f"hidden_public: {len(hidden_rows)} rows, expected {EXPECTED_HIDDEN_PUBLIC}", issues)
+        require(len(hidden_rows) == len(hidden_ids), "hidden_public: duplicate IDs", issues)
+        require(not (hidden_ids & (dev_ids | test_ids | gold_ids)), "hidden_public overlaps dev/test/gold IDs", issues)
+        forbidden = {"answer", "solution", "effective_parameters", "answer_float"}
+        leaked = [row["id"] for row in hidden_rows if forbidden & set(row)]
+        require(not leaked, f"hidden_public leaks answer-bearing fields: {leaked[:5]}", issues)
+        require(all(row.get("answer_hidden") is True for row in hidden_rows), "hidden_public rows must set answer_hidden=true", issues)
+        bad_sensitivity = [row["id"] for row in hidden_rows if row.get("mode") == "sensitivity" and not row.get("change")]
+        require(not bad_sensitivity, f"hidden_public sensitivity rows missing change: {bad_sensitivity[:5]}", issues)
+
+    private_markers = list(release_dir.rglob("*private*")) + list(release_dir.rglob("*answer*.jsonl"))
+    leaked_private = [str(path.relative_to(release_dir)) for path in private_markers if "hidden_public" not in str(path)]
+    require(not leaked_private, f"private answer-like files found in public release: {leaked_private}", issues)
+
+    return issues
+
+
+def validate_hf_loader(release_dir: Path) -> list[str]:
+    try:
+        from datasets import load_dataset
+    except ImportError:
+        return ["datasets is not installed; HF loader validation requires this dependency"]
+
+    issues: list[str] = []
+    for config, split_counts in EXPECTED.items():
+        dataset = load_dataset(str(release_dir), config)
+        observed = {split: len(dataset[split]) for split in split_counts}
+        if observed != split_counts:
+            issues.append(f"HF loader {config}: {observed}, expected {split_counts}")
+    hidden_dataset = load_dataset(str(release_dir), "hidden_public")
+    hidden_observed = len(hidden_dataset["hidden_public"])
+    if hidden_observed != EXPECTED_HIDDEN_PUBLIC:
+        issues.append(f"HF loader hidden_public: {hidden_observed}, expected {EXPECTED_HIDDEN_PUBLIC}")
+    return issues
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description="Validate CropMath release/cropmath-v1")
+    parser.add_argument("--release-dir", default="release/cropmath-v1")
+    parser.add_argument("--skip-hf-loader", action="store_true")
+    parser.add_argument(
+        "--no-scan-repo-root",
+        dest="scan_repo_root",
+        action="store_false",
+        default=True,
+        help="Skip scanning the public repo source tree for provenance residue.",
+    )
+    args = parser.parse_args()
+
+    release_dir = Path(args.release_dir).resolve()
+    repo_root = release_dir.parents[1] if release_dir.name == "cropmath-v1" else Path.cwd().resolve()
+    try:
+        release_label = str(release_dir.relative_to(Path.cwd().resolve()))
+    except ValueError:
+        release_label = str(Path(args.release_dir))
+    issues = validate_jsonl(release_dir)
+    issues.extend(validate_public_content(release_dir))
+    repo_root_issues: list[str] = []
+    if args.scan_repo_root:
+        repo_root_issues = validate_repo_root_content(repo_root)
+    hf_issues = [] if args.skip_hf_loader else validate_hf_loader(release_dir)
+    all_hard_issues = issues + repo_root_issues + hf_issues
+
+    report = {
+        "release_dir": release_label,
+        "jsonl_pass": not issues,
+        "hf_loader_pass": None if args.skip_hf_loader else not hf_issues,
+        "repo_root_scan_pass": None if not args.scan_repo_root else not repo_root_issues,
+        "issues": issues + repo_root_issues,
+        "hf_loader_issues": hf_issues,
+    }
+    print(json.dumps(report, ensure_ascii=False, indent=2))
+    if all_hard_issues:
+        raise SystemExit(1)
+
+
+if __name__ == "__main__":
+    main()

scripts/validate_formula_catalog.py

@@ -0,0 +1,75 @@
+#!/usr/bin/env python3
+"""Validate CropMath clean formula catalog metadata."""
+
+from __future__ import annotations
+
+import argparse
+import csv
+import json
+from pathlib import Path
+import re
+
+
+REQUIRED_FIELDS = [
+    "formula_id",
+    "family",
+    "name_en",
+    "unit",
+    "precision",
+    "expression",
+    "latex",
+    "math_type",
+    "sample_count",
+]
+
+EXPECTED_FORMULAS = 62
+PUBLIC_ID_RE = re.compile(r"CMF\d{3}")
+PUBLIC_CATEGORIES = {
+    "growth_yield",
+    "carbon_nitrogen_cycle",
+    "methane_emission",
+    "environmental_response",
+}
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description="Validate clean formula catalog table")
+    parser.add_argument("--path", default="release/cropmath-v1/metadata/formula_catalog.csv")
+    args = parser.parse_args()
+
+    path = Path(args.path)
+    issues: list[str] = []
+    with path.open(encoding="utf-8") as f:
+        rows = list(csv.DictReader(f))
+
+    ids = [row.get("formula_id", "") for row in rows]
+    if len(ids) != len(set(ids)):
+        issues.append("duplicate formula_id rows")
+    if len(ids) != EXPECTED_FORMULAS:
+        issues.append(f"formula count {len(ids)}, expected {EXPECTED_FORMULAS}")
+    invalid_ids = [formula_id for formula_id in ids if not PUBLIC_ID_RE.fullmatch(formula_id)]
+    if invalid_ids:
+        issues.append(f"invalid public formula IDs: {invalid_ids[:5]}")
+
+    for row in rows:
+        fid = row.get("formula_id", "")
+        missing = [field for field in REQUIRED_FIELDS if not str(row.get(field, "")).strip()]
+        if missing:
+            issues.append(f"{fid}: missing required fields {missing}")
+        if row.get("family") not in PUBLIC_CATEGORIES:
+            issues.append(f"{fid}: invalid public category {row.get('family')!r}")
+
+    report = {
+        "path": str(path),
+        "formulas": len(rows),
+        "expected_formulas": EXPECTED_FORMULAS,
+        "pass": not issues,
+        "issues": issues,
+    }
+    print(json.dumps(report, ensure_ascii=False, indent=2))
+    if issues:
+        raise SystemExit(1)
+
+
+if __name__ == "__main__":
+    main()

tests/test_dataset_loading.py

@@ -0,0 +1,54 @@
+"""Load real local configurations and check their relationships in either package."""
+
+from pathlib import Path
+
+from datasets import load_dataset
+import pytest
+
+
+ROOT = Path(__file__).resolve().parents[1]
+DATA = ROOT / "release" / "cropmath-v1" if (ROOT / "release" / "cropmath-v1").is_dir() else ROOT
+
+
+@pytest.fixture(scope="module")
+def configurations():
+    return {name: load_dataset(str(DATA), name) for name in ("default", "eval_prompts", "hidden_public")}
+
+
+def test_actual_loader_split_sizes(configurations):
+    expected = {
+        "default": {"dev": 252, "test": 751, "gold": 95},
+        "eval_prompts": {"dev": 1512, "test": 4506, "gold": 570},
+        "hidden_public": {"hidden_public": 160},
+    }
+    for name, splits in expected.items():
+        assert {split: len(rows) for split, rows in configurations[name].items()} == splits
+
+
+def test_public_pairing_and_gold_subset(configurations):
+    default = configurations["default"]
+    dev, test, gold = ({row["id"] for row in default[split]} for split in ("dev", "test", "gold"))
+    assert not dev & test
+    assert gold <= test
+    for split in ("dev", "test", "gold"):
+        rows = configurations["eval_prompts"][split]
+        grouped = {}
+        for row in rows:
+            assert (row["sample_id"], row["condition"]) not in grouped
+            grouped[row["sample_id"], row["condition"]] = row["answer_float"]
+        for row in default[split]:
+            answers = [grouped[row["id"], condition] for condition in
+                       ("C", "K_name", "K_formula", "K_domain", "K_distractor", "K_wrong")]
+            assert answers == [float(row["answer"])] * 6
+
+
+def test_auxiliary_set_has_questions_but_no_labels(configurations):
+    rows = configurations["hidden_public"]["hidden_public"]
+    ids = {row["id"] for row in rows}
+    assert len(ids) == 160
+    default = configurations["default"]
+    assert not ids & {row["id"] for split in default.values() for row in split}
+    for row in rows:
+        assert not {"answer", "answer_float", "solution", "ground_truth", "effective_parameters"} & row.keys()
+        assert row["answer_hidden"] is True
+        assert row["formula"]["expression"] and row["parameters"] and row["prompts"]

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