{"schema_version":1,"experiment_id":"eoa_inverse_innovation_exp04_retrieval_first_paired20_20260802","cell_id":"deadweight_loss_reduction__systems_cybernetics","arm":"RETRIEVAL_FIRST","round_index":0,"hypotheses":[{"hypothesis_id":"H1","title":"Load-priced control-simulation scheduling","problem":"Flat access to shared simulation clusters creates peak queues while off-peak capacity remains idle.","affected_stakeholder":"Control researchers and time-sensitive incident-analysis teams.","workflow_boundary":"From simulation-job submission through compute-slot assignment and completion.","failure_mode":"Queue rationing ignores urgency and induces synchronized demand, delay, and off-peak underuse.","unit_of_analysis":"Submitted simulation job.","causal_lever":"Vary refundable compute-credit charges with forecast load while reserving protected capacity for urgent and resource-poor users.","archetype_mapping":"Removes a timing wedge rather than raw scarcity; access safeguards and rebound monitoring preserve fairness.","expected_value":"Shorter peak waits, greater off-peak utilization, and faster completion of high-value jobs.","falsifiable_claim":"In a bounded pilot, load-priced credits will reduce median peak queue time by at least 20% without reducing protected-user completion rates by more than 3 percentage points.","diversity_rationale":"Targets a dynamic price wedge at job level, unlike approval, quota, rule-lifecycle, or matching interventions.","mechanism_slugs":["congestion_or_capacity_pricing_adjustment","impact_assessment_table"],"search_questions":["Have compute clusters tested dynamic internal credits or scarcity pricing?","What demand displacement and equity effects were measured?","Which reservation safeguards prevented urgent work from being priced out?"]},{"hypothesis_id":"H2","title":"Risk-tiered controller-change approval","problem":"Uniform serial review delays low-risk controller updates, leaving inferior parameters active after operating conditions change.","affected_stakeholder":"Control engineers, plant operators, and people exposed to operational hazards.","workflow_boundary":"From proposed controller change through validation, authorization, deployment, and rollback observation.","failure_mode":"All changes traverse the same sequential checks regardless of modeled hazard or reversibility.","unit_of_analysis":"Controller-change request.","causal_lever":"Route reversible low-risk changes through parallel review and monitored sandbox deployment while retaining full scrutiny for high-risk cases.","archetype_mapping":"Separates procedural delay from substantive safety review and tests a lighter pathway within a reversible boundary.","expected_value":"Faster adaptation to disturbances without higher unsafe-event or rollback rates.","falsifiable_claim":"Eligible changes will reach deployment at least 30% faster, with no statistically detectable increase in predefined safety violations over six months.","diversity_rationale":"Changes an approval process for discrete modifications, rather than prices, resource assignments, standing rules, or partner discovery.","mechanism_slugs":["permit_or_approval_streamlining","regulatory_simplification_pilot","distortion_reduction_review"],"search_questions":["Which cyber-physical organizations already risk-tier controller changes?","How are low-risk eligibility and safety equivalence defined?","Do faster pathways increase rollback, incident, or gaming rates?"]},{"hypothesis_id":"H3","title":"Transferable telemetry-capacity quotas","problem":"Fixed per-service telemetry quotas leave storage idle in some services while forcing high-risk services to discard diagnostically valuable signals.","affected_stakeholder":"Site-reliability engineers, service owners, and users affected by outages.","workflow_boundary":"From telemetry generation through admission, retention, and incident retrieval.","failure_mode":"Grandfathered quotas cannot move with changing diagnostic value, risk, or service load.","unit_of_analysis":"Service-day telemetry allocation.","causal_lever":"Permit bounded quota transfers using risk-weighted bids, minimum observability floors, and automatic recall during incidents.","archetype_mapping":"Repairs a stale allocation rule while preserving the aggregate capacity cap and minimum safety observability.","expected_value":"Higher diagnostic coverage and lower unused retention capacity without increasing total storage.","falsifiable_claim":"Transferability will cut unused allocated capacity by 25% and reduce quota-caused signal drops by 20% without worsening incident detection time.","diversity_rationale":"Targets quantity allocation across organizational services, distinct from temporal pricing, approvals, expiry rules, and matching.","mechanism_slugs":["quota_or_allocation_rule_review","impact_assessment_table","cost_benefit_assessment_protocol"],"search_questions":["Are transferable observability or data-retention quotas documented?","Which allocation metrics predict telemetry value during incidents?","What floors or recall rules prevent strategic under-observability?"]},{"hypothesis_id":"H4","title":"Sunsetting obsolete interface constraints","problem":"Compatibility requirements persist after their protected interoperability purpose has faded, accumulating complexity and blocking safer protocol evolution.","affected_stakeholder":"Standards maintainers, implementers, and users dependent on interoperable systems.","workflow_boundary":"From adoption of a normative interface requirement through version maintenance, renewal, revision, or retirement.","failure_mode":"Requirements persist by default because no scheduled evidence test distinguishes active dependencies from legacy inertia.","unit_of_analysis":"Normative interface requirement at a specification revision.","causal_lever":"Attach staged expiry and renewal tests based on measured dependency, migration cost, security exposure, and producer-consumer tolerance.","archetype_mapping":"Reverses the persistence default while preserving requirements that still protect interoperability or vulnerable adopters.","expected_value":"Lower implementation burden and attack surface with controlled ecosystem migration.","falsifiable_claim":"A sunset review will identify removable constraints whose retirement lowers conformance effort by at least 10% without increasing interoperability failures beyond a preset margin.","diversity_rationale":"Intervenes in the lifecycle of standing specifications and uses interface-level evidence, not operational queues or allocations.","mechanism_slugs":["sunset_clause_review","cost_benefit_assessment_protocol","impact_assessment_table"],"search_questions":["Which standards bodies sunset individual normative requirements?","How are active dependencies and asymmetric interface tolerance measured?","What retirements reduced complexity without fragmenting interoperability?"]},{"hypothesis_id":"H5","title":"Cross-lab disturbance-testbed clearinghouse","problem":"Teams needing rare disturbance tests cannot identify compatible underused testbeds, so validation remains incomplete despite available capacity.","affected_stakeholder":"Systems researchers, testbed operators, and downstream adopters of validated controllers.","workflow_boundary":"From test requirement specification through compatibility screening, slot assignment, execution, and result return.","failure_mode":"Information silos and heterogeneous testbed descriptions prevent feasible demand-supply pairings.","unit_of_analysis":"Proposed experiment-to-testbed pairing.","causal_lever":"Create a clearinghouse with standardized capability descriptors, constraint-aware matching, and participation rules discouraging slot withholding.","archetype_mapping":"Recovers latent mutually beneficial use by repairing pairing failure while retaining safety, ownership, and access constraints.","expected_value":"More completed stress tests, higher testbed utilization, and broader disturbance coverage.","falsifiable_claim":"Compared with existing bilateral discovery, the clearinghouse will increase feasible completed pairings by 20% without raising testbed safety exceptions.","diversity_rationale":"Targets cross-institutional compatibility matching at pairing level, unlike internal price, approval, quota, or standards-lifecycle wedges.","mechanism_slugs":["matching_improvement_program","distortion_reduction_review","impact_assessment_table"],"search_questions":["Do shared experimental facilities use constraint-aware clearinghouses?","Which descriptors reliably establish testbed-experiment compatibility?","What participation rules prevent withholding, ranking games, or unsafe matches?"]}]}