{"schema_version":1,"experiment_id":"eoa_inverse_innovation_exp03_full320_20260801","cell_id":"negative_space_design__data_science","trajectory_id":"R","attempt_index":0,"candidate_sha256":"dfecc5de60df0e2ad95ba2353f990e7d7ae38ccb360b724cc9d2764a78a420fd","gates":{"G1":{"status":"PASS","reason":"The monitoring failure is defined independently in domain terms, with affected actors, observable dashboard states, consequences, and a falsifier separating crowding from missing metrics, invalid thresholds, training gaps, and source-data defects."},"G2":{"status":"PASS","reason":"The proposal preserves the archetype's defining structure: identified attention competitors are reversibly omitted, an absence boundary protects space around the focal exception, the space has an explicit positive-form relationship, and necessary context remains recoverable."},"G3":{"status":"PASS","reason":"The causal chain connects measurable attention competition and ambiguous empty states to reversible demotion, protected spacing, explicit state diagnosis, and reviewer detection outcomes. Comparative effectiveness remains correctly bounded as a hypothesis."},"G4":{"status":"PASS","reason":"Every archetype component has a concrete domain realization, and selected mechanisms have distinct causal, operational, or safety roles with informative counterfactual-removal statements. Rejected and incompatible mechanisms are handled coherently."},"G5":{"status":"PASS","reason":"The candidate distinguishes inference from hypothesis, declares prior art unsearched, avoids presenting effectiveness as established, and proposes empirical comparison rather than relying on unsupported authority."},"G6":{"status":"PASS","reason":"The problem and intervention have separate falsifiers. The baseline, severity-ranked rival, matched-information comparison, outcomes, rejection condition, and rollback criteria make the proposal discriminating and testable."},"G7":{"status":"PASS","reason":"Authority is appropriately split between prototype authorization and production control. The first test is read-only and replay-based, excluded actions protect live operations and evidence, and explicit halt conditions cover detectability, interpretation, access, and accessibility."}},"scores":{"structural_fit":{"score":4,"reason":"The proposal uses protected absence as an active perceptual structure rather than as generic simplification or decorative minimalism."},"domain_fidelity":{"score":4,"reason":"The formulation reflects production monitoring realities, including drift, calibration, data quality, telemetry freshness, permissions, filters, uncertainty, audit evidence, and expert side-by-side review needs."},"causal_plausibility":{"score":3,"reason":"The attention-isolation and empty-state mechanisms are coherent and measurable, but their advantage over prioritization alone remains empirically unresolved."},"component_translation":{"score":4,"reason":"The component map is complete, specific, mutually coherent, and reinforced by appropriately selected mechanisms and recoverability constraints."},"adversarial_survival":{"score":4,"reason":"The candidate confronts dense-view expertise, navigation costs, constrained screens, telemetry-failure ambiguity, severity-assumption bias, accessibility failure, and clutter recurrence."},"reframing_gain":{"score":4,"reason":"It reframes dashboard improvement from adding stronger alerts to protecting perceptual room and making absence diagnostically explicit, yielding a distinct intervention and rival comparison."},"practicality_testability":{"score":4,"reason":"A bounded shadow simulation with replayed cases, representative reviewers, concrete outcomes, a strong rival, and explicit stopping criteria is feasible and informative."},"expected_value_risk":{"score":4,"reason":"The proposed first step offers useful comparative evidence without altering live alerts or decisions, while preserving critical context and enabling immediate rollback."},"novelty_evidence":{"score":1,"reason":"The composition is plausibly distinctive, but the declared unsearched prior-art status supplies little evidence that comparable monitoring-interface patterns do not already exist."}},"weighted_total":92.5,"disposition":"DEEP_RESEARCH","fabrication_findings":[],"weak_dimensions":["novelty_evidence"],"actionable_critique":[{"priority":"MEDIUM","issue":"Novelty is asserted only at the level of a plausible composition, with no prior-art evidence.","repair":"Before claiming novelty, compare the full mechanism composition and protected-absence causal lever against monitoring-dashboard research, commercial design patterns, and human-factors studies.","evidence_boundary":"This closed-book evaluation supports structural quality and testability, not originality or empirical superiority."}],"repairs":[],"improvement_attribution":{"kind":"NONE","reason":"This is an original attempt with no prior candidate, changed problem identifier, changed causal-lever identifier, or registered repair from which improvement could be attributed."},"trajectory_replacement":false,"arm_guess":"MECHANISM_PACKET","recommendation":"SUCCESS","tester_summary":"The candidate passes every reject-first gate and presents a domain-grounded, safety-bounded, falsifiable application of protected absence to model-monitoring dashboards. Deep research is warranted primarily to establish prior art and comparative effectiveness."}