{"schema_version":1,"experiment_id":"eoa_inverse_innovation_exp11_mechanism_context_external20_20260804","cell_id":"negative_space_design__computer_science","judge_id":"J2","item_assessments":[{"opaque_id":"negative_space_design__computer_science__B","supported_problem":3,"external_distinctiveness":4,"testability":4,"researchability":4,"evidence_quality":4,"fatal_issue":null},{"opaque_id":"negative_space_design__computer_science__C","supported_problem":3,"external_distinctiveness":2,"testability":4,"researchability":3,"evidence_quality":4,"fatal_issue":null},{"opaque_id":"negative_space_design__computer_science__A","supported_problem":4,"external_distinctiveness":1,"testability":4,"researchability":2,"evidence_quality":4,"fatal_issue":null}],"pairwise_comparisons":[{"pair_id":"B_vs_C","left_id":"negative_space_design__computer_science__B","right_id":"negative_space_design__computer_science__C","preference":"LEFT","confidence":"HIGH","rationale":"B retains a sharper unresolved contrast: verification semantics, evidence, ordering, and controls are fixed while spacing and duplicate chrome are varied, with a typography-only rival, dual decision endpoints, an evidence-recovery margin, and an UNKNOWN-safety bound. C addresses a credible interruption problem, but conditional withholding, snooze, debounce, manual invocation, and do-not-disturb modes already closely cover both its problem and lever, leaving a narrower comparative increment."},{"pair_id":"B_vs_A","left_id":"negative_space_design__computer_science__B","right_id":"negative_space_design__computer_science__A","preference":"LEFT","confidence":"HIGH","rationale":"A has the best-supported underlying problem, but dark-screen principles, severe-event-only consoles, duplicate consolidation, explicit no-data states, and recoverable histories make its package established practice; its remaining value is mainly local comparative effectiveness. B has weaker baseline-prevalence evidence but substantially more external distinctiveness and an equally bounded, safety-conscious falsification study."},{"pair_id":"C_vs_A","left_id":"negative_space_design__computer_science__C","right_id":"negative_space_design__computer_science__A","preference":"LEFT","confidence":"MODERATE","rationale":"Both face close prior art, but C preserves a meaningful unresolved question about transparent automatic cooldowns after specified developer events versus continuous eligibility, relevance filtering, debounce, and manual snooze. A's causal package is already represented in longstanding guidance, controlled alarm research, and deployed consoles, so its proposed study is worthwhile chiefly for context-specific effect estimation rather than a distinctive research contribution."}],"overall_top_choice":"negative_space_design__computer_science__B","overall_rationale":"B offers the strongest combination of a meaningful partly supported problem, a precise contrastive claim not resolved by the retained adjacent art, genuine outcome and safety falsifiers, a bounded controlled study, credible authorizers, and strong multi-source evidence. Its principal uncertainty—whether crowding causes enough baseline verification error—can itself be resolved by the proposed experiment and is less damaging than C's extensive lever-level product overlap or A's established-practice collision.","blinding_limitations":"Assessment used only the three supplied preserved records and their bounded public-web scrutiny. It did not verify sources independently, infer treatment identity, inspect other cells or prior outcomes, or treat prior-art disposition labels as a fixed ranking. Scores reflect comparative research value under the supplied evidence rather than world novelty, patentability, market value, or production readiness."}