{"schema_version":1,"experiment_id":"eoa_inverse_innovation_exp11_mechanism_context_external20_20260804","cell_id":"computability_boundary_mapping__philosophy","judge_id":"J2","item_assessments":[{"opaque_id":"computability_boundary_mapping__philosophy__B","supported_problem":4,"external_distinctiveness":2,"testability":5,"researchability":4,"evidence_quality":5,"fatal_issue":null},{"opaque_id":"computability_boundary_mapping__philosophy__A","supported_problem":3,"external_distinctiveness":3,"testability":4,"researchability":3,"evidence_quality":4,"fatal_issue":null},{"opaque_id":"computability_boundary_mapping__philosophy__C","supported_problem":2,"external_distinctiveness":3,"testability":4,"researchability":2,"evidence_quality":4,"fatal_issue":"No actual platform making the hypothesized universal Boolean guarantee, converting timeouts to false, or authorizing the study was identified."}],"pairwise_comparisons":[{"pair_id":"B_vs_A","left_id":"computability_boundary_mapping__philosophy__B","right_id":"computability_boundary_mapping__philosophy__A","preference":"LEFT","confidence":"MODERATE","rationale":"B has the stronger externally grounded problem and adopter path: Oak supplies a philosophy-capable instance of ambiguous invalidity/resource-limit reporting, and relevant operators are identifiable. Its mechanisms closely duplicate established standards, limiting distinctiveness, but the 60-pair contrastive pilot is sharper and less conditional than A's study, which first requires verification that a forced-binary platform problem exists."},{"pair_id":"B_vs_C","left_id":"computability_boundary_mapping__philosophy__B","right_id":"computability_boundary_mapping__philosophy__C","preference":"LEFT","confidence":"HIGH","rationale":"Both largely transfer established fragment-scoping and abstention practices, but B links them to stronger product evidence, identifiable technical adopters, explicit outcome metrics, and a well-bounded pilot. C lacks evidence for both the asserted deployment problem and an authorized adopter, making its otherwise falsifiable audit premature."},{"pair_id":"A_vs_C","left_id":"computability_boundary_mapping__philosophy__A","right_id":"computability_boundary_mapping__philosophy__C","preference":"LEFT","confidence":"MODERATE","rationale":"A remains conditional, but it identifies a concrete platform operator, specifies a more discriminating 120-case shadow test, and measures forced-binary errors, soundness, coverage, and user interpretation. C has a smaller bounded audit but no demonstrated target workflow or authorizer and weaker evidence that its proposed outcomes address a real deployment problem."}],"overall_top_choice":"computability_boundary_mapping__philosophy__B","overall_rationale":"B is the most worthwhile research candidate because it combines the best-supported domain problem, the clearest adopter and authority path, high-quality direct and standards evidence, and a reversible falsifiable pilot. Its external distinctiveness is only incremental—the core mechanisms are established automated-reasoning practice—but that limitation is preferable to the more distinctive-looking yet insufficiently evidenced target conditions in A and C.","blinding_limitations":"The records describe hypothetical or incompletely documented platforms, and the searches did not inspect private logs, code, contracts, or adopter intent. Scores therefore assess the supplied public-web record and bounded incremental research value, not world novelty, prevalence, market value, or realized impact."}