{"schema_version":1,"assessment_id":"eoa_inverse_innovation_exp03_opportunity320_20260801","source_experiment_id":"eoa_inverse_innovation_exp03_full320_20260801","cell_id":"computability_boundary_mapping__sociology_anthropology","archetype_slug":"computability_boundary_mapping","domain_slug":"sociology_anthropology","title":"Model-relative emergence analysis with explicit non-Boolean fallbacks","opportunity_summary":"Replace an asserted universal YES/NO emergence decider for arbitrary executable agent-based models with audited scope classification: exact answers for an enforceable finite-state fragment and witnessed YES, bounded UNKNOWN, or out-of-scope labels elsewhere. The candidate directly addresses timeout-as-NO and finite-example-to-universal errors, but its value remains conditional on the actual model class being unrestricted, a stable emergence predicate, and an independently verified reduction or useful restricted fragment.","adopter_authorizer":"The simulation program lead can authorize research-interface changes; independent review must authorize impossibility language, and neither party is authorized to convert model verdicts into decisions over represented communities.","scores":{"meaningful_impact":{"score":3,"rationale":"Preventing categorical but unjustified simulation claims could protect research quality and downstream policy interpretation, but the packet provides no evidence about prevalence, realized harm, or the number of affected projects."},"stakeholder_pull":{"score":2,"rationale":"Researchers, engineers, reviewers, modeled communities, and policy users are identifiable beneficiaries, but the sealed candidate contains no expressed demand, adoption commitment, or evidence that programs recognize the issue as a priority."},"incremental_advantage":{"score":4,"rationale":"Compared with Boolean timeouts and example-based universal claims, enforced scope labels and UNKNOWN handling directly target the specified classification errors; they also add a formal-solvability check that the stated construct-validity rival does not provide."},"distinctiveness_plausibility":{"score":3,"rationale":"The combination of checked reduction, enforceable decidable fragments, and guarantee-labeled routing is coherent and differentiated from the named rival, but prior art is explicitly unsearched and world novelty is unmeasured."},"technical_implementability":{"score":3,"rationale":"Auditing one language, testing a small finite corpus, and adding labels appear bounded, while a valid reduction, stable predicate, enforceable fragment, and tractable exhaustive analysis are unresolved technical dependencies."},"adoption_authority_feasibility":{"score":4,"rationale":"The packet identifies a program lead with interface authority, assigns independent review for impossibility claims, excludes consequential policy deployment, and supplies halt and rollback conditions; actual organizational willingness is untested."},"evidence_readiness":{"score":3,"rationale":"The candidate supplies separate problem and intervention falsifiers, a concrete comparison, and explicit negative tests, but remains a hypothesis with no checked reduction, corpus results, or external validation."},"safety_net_benefit":{"score":4,"rationale":"Preserving UNKNOWN and out-of-scope states, prohibiting timeout-as-NO, versioning guarantees, and barring model-to-world policy inference provide a strong research safety net, although downstream users may ignore or relabel abstentions."},"scalability":{"score":3,"rationale":"The classification pattern could transfer across simulation projects, but proofs, predicates, fragment definitions, and enforcement would likely be model-language-specific, and decidable fragments may still face severe state-space growth."}},"score_confidence":"MODERATE","costs":{"first_evidence":{"band_2026_usd":"10K_TO_50K","scope":"Audit one model language and one emergence predicate, formalize the claimed guarantee, review a candidate reduction, and compare the existing analyzer with exhaustive search on a small finite corpus.","confidence":"LOW","assumptions":["Existing analyzer, language specification, and representative finite models are accessible.","The step is research-only and does not integrate with consequential workflows.","Labor includes simulation expertise, formal-methods review, corpus preparation, and evaluation.","No exact resource requirements are supplied in the sealed candidate."]},"initial_deployment_startup":{"band_2026_usd":"50K_TO_250K","scope":"Implement and verify fragment admission checks, non-Boolean routing, versioned guarantee labels, audit records, and rollback behavior for one simulation program.","confidence":"LOW","assumptions":["One existing platform is modified rather than replaced.","Independent verification and basic governance documentation are included.","The platform exposes sufficient semantics and interfaces for enforceable classification.","No policy-facing deployment or broad model migration is included."]},"operational_launch":{"band_2026_usd":"50K_TO_250K","scope":"Launch the revised research interface within one program, including validation, reviewer procedures, staff training, migration of selected models, monitoring for relabeled UNKNOWN results, and launch evaluation.","confidence":"LOW","assumptions":["Launch remains confined to research claims.","A limited number of model families and users require migration.","Independent reviewers and affected research teams can participate.","Representation-fidelity review is bounded rather than a comprehensive community-engagement program."]},"annual_recurring":{"band_2026_usd":"10K_TO_50K","scope":"Maintain language and predicate versions, review boundary changes, monitor abstention handling and claim wording, rerun regression corpora, and support periodic independent review for one program.","confidence":"LOW","assumptions":["The model language and fragment change infrequently.","Monitoring uses existing research-governance infrastructure.","Major new reductions, platform rewrites, and consequential-use reviews are excluded.","State-space computation remains limited to approved research workloads."]}},"research_burden":"HIGH","earliest_credible_horizon":"3_TO_12_MONTHS","pipeline_gates":{"recognizable_externally_supportable_problem":{"status":"YES","reason":"The candidate specifies an independently recognizable mismatch between an unrestricted executable model class, a total terminating guarantee, and an interface that converts timeouts into negative verdicts; external prevalence remains unmeasured but is not needed to recognize the stated problem."},"identifiable_adopter_or_authorizer":{"status":"YES","reason":"The simulation program lead is explicitly authorized to approve research-interface changes, with independent review required for impossibility language."},"distinct_testable_incremental_claim":{"status":"YES","reason":"The proposal claims that enforced finite-fragment admission plus witnessed YES, bounded UNKNOWN, and out-of-scope labels will improve classification errors, abstention handling, and claim wording relative to the current Boolean timeout baseline."},"bounded_next_evidence_step":{"status":"YES","reason":"The packet authorizes an audit of one language and predicate, a checked candidate reduction, and comparison against exhaustive search on a small finite corpus, with proof rejection and failure to improve errors or wording as falsifiers."},"no_unresolved_safety_or_authority_stop":{"status":"YES","reason":"The candidate confines the step to research, requires independent review, forbids consequential policy use and model-to-world inevitability claims, and provides explicit halt and rollback conditions."},"implementation_cost_scope_and_range":{"status":"UNCERTAIN","reason":"The candidate identifies implementation components but supplies no staffing, platform architecture, corpus size, integration complexity, or resource evidence sufficient to validate the estimated cost bands."}},"blocking_evidence":["Whether the actual requirement admits unrestricted models and horizons rather than an enforceably finite, bounded class.","Whether a stable formal emergence predicate can be specified for the selected model language.","Independent verification that the proposed reduction preserves the required behavior.","Evidence that the restricted fragment can be enforced and analyzed at useful scale without silently excluding hard inputs.","Comparative evidence that labeled fallbacks reduce classification errors or misleading claim wording relative to the Boolean timeout baseline.","Adopter and reviewer willingness to preserve UNKNOWN and out-of-scope labels in practice.","External evidence concerning prior art and distinctiveness."],"next_evidence_step":"Conduct a research-only audit of one model language and one emergence predicate: formalize the current universal guarantee, have an independent reviewer check a candidate halting-to-emergence reduction, define an enforceable finite fragment, and compare the current Boolean analyzer with exhaustive search and labeled fallback routing on a small finite corpus. Stop the line of inquiry if the actual requirement is demonstrably finite and bounded; reject the intervention if the reduction fails and the fallback design does not improve classification errors, abstention handling, or claim wording.","research_questions":["Does the admitted model language permit unbounded computation or an unbounded horizon under the actual requirement?","Can the selected collective outcome be represented by a stable, mechanically checkable predicate without conflating model reachability with real-world social interpretation?","Does independent review validate the reduction and its preservation assumptions?","Which syntactic or semantic fragment is both enforceably decidable and useful to the simulation program?","How often does the current analyzer convert timeout or proof failure into NO, and does labeled routing correct those cases on the comparison corpus?","Will reviewers and program leaders preserve UNKNOWN and out-of-scope labels when results are communicated downstream?","What prior systems or research already implement comparable scope checks, abstention labels, or model-relative guarantees?"],"recommendation":"PARTNERED_RESEARCH","uncertainty_constraints":["Closed-book assessment provides no external evidence of problem prevalence, stakeholder demand, prior art, market size, or realized impact.","The computability conclusion is conditional on a valid checked reduction and an actually unrestricted admitted model class.","Finite decidability does not imply practical tractability because exhaustive state spaces may remain infeasible.","A formal model verdict cannot establish the corresponding empirical claim about open social systems.","Cost bands are resource-equivalent planning ranges, not observed or exact costs.","The proposal may lose value if the real requirement is already finite and bounded or if no stable emergence predicate exists."],"closed_book_prior_art_boundary":"Prior art is explicitly UNSEARCHED. This assessment makes no claim that the mechanism is novel, rare, prevalent, commercially differentiated, or absent from existing simulation platforms, formal-verification systems, or research-governance practices."}