{"schema_version":1,"experiment_id":"eoa_inverse_innovation_exp07_retrospective_selector60_20260803","cell_code":"E7C027","selector_replication":1,"assessments":[{"blind_id":"CANDIDATE_A","problem_reality_importance":57,"causal_archetype_fit":86,"distinctiveness_prior_art_resilience":46,"operational_specificity":91,"falsifiability_test_quality":89,"adopter_partner_path":76,"deployability_complexity":64,"authority_safety_reversibility":94,"strict_potential":57,"empirical_partner_potential":76,"scrutiny_priority":62,"biggest_visible_risk":"The claimed transmission, storage, and attention bottleneck may not be binding enough to justify a synchronized predictive codec and its substantial governance overhead.","rationale":"The proposal is unusually specific, reconstructive, reversible, and supported by a decision-changing shadow test. The predictive residual is genuinely load-bearing rather than decorative. However, Raman spectra are bounded data objects, and the text does not establish that full-spectrum movement or review is a consequential constraint that ordinary compression, visualization, or alerting cannot address. Its broad mechanism set also makes the remaining contrastive claim vulnerable to looking like predictive compression plus anomaly routing."},{"blind_id":"CANDIDATE_B","problem_reality_importance":79,"causal_archetype_fit":79,"distinctiveness_prior_art_resilience":42,"operational_specificity":86,"falsifiability_test_quality":88,"adopter_partner_path":85,"deployability_complexity":66,"authority_safety_reversibility":93,"strict_potential":58,"empirical_partner_potential":87,"scrutiny_priority":74,"biggest_visible_risk":"The residual-first queue may collapse under scrutiny into familiar model-based triage, active learning, or anomaly review, with reconstruction adding little for heterogeneous characterization packages.","rationale":"Scientist attention and follow-up capacity are credible scarce resources, and a materials campaign offers a clear partner, bounded matrix, preserved raw evidence, and a strong shadow comparison. The proposal protects unfamiliar features and specifies owned follow-up actions well. Its weakness is conceptual breadth: numerical, categorical, peak, missingness, and raw-file outputs are only partly reconstructable by prediction plus residual, while much of the operational value could arise from established uncertainty and anomaly prioritization rather than the claimed residual architecture."},{"blind_id":"CANDIDATE_C","problem_reality_importance":91,"causal_archetype_fit":84,"distinctiveness_prior_art_resilience":24,"operational_specificity":92,"falsifiability_test_quality":94,"adopter_partner_path":88,"deployability_complexity":73,"authority_safety_reversibility":92,"strict_potential":48,"empirical_partner_potential":89,"scrutiny_priority":71,"biggest_visible_risk":"Learning reference-minus-baseline corrections with uncertainty and active reference queries looks highly vulnerable to well-developed delta-learning, multifidelity surrogate, and active-learning prior art.","rationale":"This addresses a consequential compute-versus-fidelity problem with precise targets, authoritative reference observations, bounded scope, independent audits, explicit invariants, and an excellent equal-budget comparison against both a direct surrogate and the uncorrected baseline. It is especially attractive as an empirical-partner study because the decisive evidence can be generated offline without operational risk. Strict potential is limited because the core numerical correction architecture appears known-looking from the proposal itself, and its extra governance may improve implementation without preserving a meaningful contrastive claim."},{"blind_id":"CANDIDATE_D","problem_reality_importance":87,"causal_archetype_fit":95,"distinctiveness_prior_art_resilience":68,"operational_specificity":93,"falsifiability_test_quality":92,"adopter_partner_path":84,"deployability_complexity":69,"authority_safety_reversibility":95,"strict_potential":78,"empirical_partner_potential":88,"scrutiny_priority":88,"biggest_visible_risk":"A real obstruction synchronized with commanded motion may resemble the predicted self-generated response and be cancelled while all model-validity checks remain nominal.","rationale":"The outgoing command is causally essential: it supplies information unavailable to an ordinary signal threshold or generic anomaly detector and directly supports separation of self-generated from external interaction. The proposal defines synchronization, reconstruction, independent raw audits, protected safety bypasses, slow updates, named operator actions, and a safe shadow test with controlled disturbances capable of falsifying the central claim. Although observers and feedforward cancellation create prior-art exposure and operational timing is demanding, this candidate has the strongest combination of consequential problem, distinctive mechanism, reversibility, and partner-resolvable uncertainty."}],"rank_order":["CANDIDATE_D","CANDIDATE_B","CANDIDATE_C","CANDIDATE_A"],"top_choice":"CANDIDATE_D","portfolio_observation":"All four proposals are highly governed residual architectures with strong shadow tests, so the main discriminator is whether prediction error supplies unique causal leverage rather than merely repackaging compression, triage, or surrogate modeling. D has the clearest such leverage through the command efference copy. C offers the cleanest empirical evaluation but the greatest visible prior-art exposure; B is partner-ready but conceptually diffuse; A is technically polished but rests on the least established binding constraint.","confidence":"HIGH"}