{
  "schema": "frontierlab.method-evaluation-draft.v1",
  "recorded_date_taipei": "2026-10-28",
  "source_handoff": "docs/runs/nim_method_handoff_20261028.json",
  "status": "RESEARCHER_SELECTED_M2_READY_FOR_FORMAL_EVALUATION",
  "selected_candidate_id": "M2",
  "selection_rationale": "Researcher selected M2 because its structure-based computational design creates the clearest in-silico-to-in-vitro AI-for-Science demonstration: an AI agent can reason over a structural model, prioritize dual-pH histidine-scanning variants, and hand candidates to experimental Fab, cell, full-antibody and functional validation. This produces a stronger end-to-end FrontierLab narrative than M1, whose core search loop depends more heavily on physical library generation and FACS screening. M1 is retained as a comparator because it can reveal histidine-independent pH-switching solutions and therefore exposes the selected method's histidine-centered bias. M2's assay limitations are treated as a validation requirement rather than ignored: downstream planning should include an orthogonal biophysical check such as SPR on monomeric Fab where feasible to distinguish intrinsic affinity from avidity/stoichiometry effects.",
  "candidates": [
    {
      "candidate_id": "M1",
      "name": "Directed evolution with yeast surface display and alternating-pH selection",
      "evidence_ids": [
        "PMC4314675"
      ],
      "scope": "Use a displayed Fcab library with positive selection for Her2 binding at pH 7.4 and negative selection/non-binding at pH 6.0, followed by clone-level pH-dependent binding characterization.",
      "comparison": {
        "expected_value": "Directly explores sequence space and can discover pH-sensitive variants without assuming histidine substitutions are required.",
        "resources": "Yeast display library, flow cytometric sorting, recombinant Her2, soluble-expression workflow and downstream binding/stability assays.",
        "validation": "Compare binding at pH 6.0 versus 7.4, then verify soluble-protein/cell binding and stability with independent repeats.",
        "limitations": "Empirical and resource-intensive; findings may depend strongly on library design, target, antibody format and selection thresholds.",
        "novelty": "Useful discovery-oriented comparator because it can reveal non-obvious pH-switching sequence solutions."
      },
      "reproducibility_checks": {
        "data": "UNKNOWN_PENDING_FULL_TEXT_EXTRACTION",
        "code": "NOT_APPLICABLE_OR_NOT_YET_IDENTIFIED",
        "environment": "UNKNOWN_PENDING_FULL_TEXT_EXTRACTION",
        "parameters": "PARTIALLY_DOCUMENTED_IN_SOURCE",
        "protocol": "DOCUMENTED_IN_SOURCE_NOT_REPRODUCED",
        "metrics": "DOCUMENTED_IN_SOURCE_NOT_REPRODUCED"
      },
      "executed_in_frontierlab": false
    },
    {
      "candidate_id": "M2",
      "name": "Structure-based dual-pH histidine-scanning computational design",
      "evidence_ids": [
        "PMC6927761"
      ],
      "scope": "Use a structure-based antibody design platform with dual-pH histidine-scanning mutagenesis to propose variants, then test Fab and full-size antibody binding across acidic and physiological pH.",
      "comparison": {
        "expected_value": "Provides a targeted, mechanism-guided design route that can reduce the experimental search space and optimize acidic-pH selectivity.",
        "resources": "Antibody-antigen structural model, computational design platform, recombinant expression, binding assays, cell-based validation and functional spheroid assays.",
        "validation": "Measure recombinant and cell-surface binding across pH, compare parental controls, inspect Her2-density effects and confirm functional activity under acidic versus physiological conditions.",
        "limitations": "Depends on structural information and histidine-centered design assumptions; assay stoichiometry and avidity can affect apparent affinity estimates.",
        "novelty": "Useful design-oriented comparator because it prospectively links structural modeling to pH-selective antibody engineering."
      },
      "reproducibility_checks": {
        "data": "UNKNOWN_PENDING_FULL_TEXT_EXTRACTION",
        "code": "UNKNOWN_PLATFORM_AVAILABILITY",
        "environment": "UNKNOWN_PENDING_FULL_TEXT_EXTRACTION",
        "parameters": "PARTIALLY_DOCUMENTED_IN_SOURCE",
        "protocol": "DOCUMENTED_IN_SOURCE_NOT_REPRODUCED",
        "metrics": "DOCUMENTED_IN_SOURCE_NOT_REPRODUCED"
      },
      "executed_in_frontierlab": false
    }
  ],
  "automatic_selection": false,
  "automatic_planning": false,
  "scientific_execution_verified": false,
  "note": "Stage 4 researcher selection recorded. M2 is selected for the FrontierLab demo path; M1 remains a comparator. Planning remains unapproved and blocked.",
  "researcher_decision": {
    "reviewer": "Jaycee871",
    "recorded_date_taipei": "2026-10-28",
    "decision": "SELECT_M2",
    "automatic_selection": false,
    "planning_approved": false,
    "key_reasoning": [
      "M2 provides the strongest in-silico-to-in-vitro AI-for-Science demonstration space.",
      "M2 supports a clearer end-to-end computational-design-to-biological-validation storyline.",
      "M1 remains useful as a comparator but depends more heavily on physical library generation and FACS screening.",
      "Avidity/stoichiometry limitations should become explicit downstream validation checks rather than be hidden."
    ],
    "proposed_downstream_check": "Where feasible, use an orthogonal assay such as SPR on monomeric Fab to distinguish intrinsic affinity from avidity effects."
  }
}