{"schema_version":1,"assessment_id":"eoa_inverse_innovation_exp03_opportunity320_20260801","source_experiment_id":"eoa_inverse_innovation_exp03_full320_20260801","cell_id":"deadweight_loss_reduction__information_theory","archetype_slug":"deadweight_loss_reduction","domain_slug":"information_theory","title":"Constraint-Preserving Adaptive Channel Allocation","opportunity_summary":"Test whether a channel-state- and queue-aware scheduler can recover transmission opportunities stranded by static allocations while preserving power, error, latency, privacy, fairness, and minimum-service constraints. The packet provides a clear mechanism and falsifiable comparison, but supplies no evidence about problem prevalence, realized gains, stakeholder demand, or novelty relative to existing scheduling methods.","adopter_authorizer":"The network operator or protocol governance body controlling scheduling, subject to service, privacy, reliability, safety, and affected-party commitments.","scores":{"meaningful_impact":{"score":3,"rationale":"Recovering stranded feasible opportunities could improve reliable throughput, outage, or delay without adding physical capacity, but the packet provides no evidence about the frequency, scale, or value of the alleged allocation loss."},"stakeholder_pull":{"score":3,"rationale":"Operators and affected traffic classes have plausible reasons to value better utilization and service, yet no operator demand, user preference, procurement interest, or observed operational pain is supplied."},"incremental_advantage":{"score":4,"rationale":"The proposal directly targets allocation loss that added capacity or stronger coding would not correct, and it requires comparison under unchanged protection limits; the magnitude and robustness of the incremental gain remain untested."},"distinctiveness_plausibility":{"score":2,"rationale":"The composition of channel-state information, queues, congestion shadow prices, and safeguarded adaptive scheduling is clearly specified, but prior art is explicitly unsearched and the packet itself identifies established adaptive-scheduling and network-utility work as a likely boundary."},"technical_implementability":{"score":4,"rationale":"Logged replay, measurable channel and queue state, a static-scheduler comparator, hard thresholds, and rollback make a bounded implementation credible. Channel-estimation error, signaling overhead, oscillation, computation, and privacy requirements could still defeat it."},"adoption_authority_feasibility":{"score":4,"rationale":"A network operator or protocol governance body is identifiable and would control the scheduler, while excluded actions and protected commitments are explicit. Actual authority over traffic weights, privacy changes, and service commitments still requires confirmation."},"evidence_readiness":{"score":5,"rationale":"The packet defines observable states, a baseline, representative-trace testing, protected metrics, an independent problem falsifier, an intervention falsifier, and rollback conditions suitable for a decision-relevant logged comparison."},"safety_net_benefit":{"score":4,"rationale":"Hard minima, unchanged reliability and privacy limits, predefined halt thresholds, and immediate restoration of the baseline provide meaningful protection against starvation or service degradation, although aggregate optimization could still conceal distributional harm."},"scalability":{"score":3,"rationale":"Scheduler-based adaptation could in principle extend across links and flows, but scalability is uncertain because state collection, computation, signaling, protocol heterogeneity, strategic classification, and governance burdens are not quantified."}},"score_confidence":"MODERATE","costs":{"first_evidence":{"band_2026_usd":"50K_TO_250K","scope":"Obtain and prepare representative traces, implement an offline adaptive-scheduler prototype, preregister metrics and thresholds, replay identical traffic and channel conditions against the static baseline, and analyze protected-flow outcomes.","confidence":"LOW","assumptions":["A partner already records usable channel, queue, error, and service-class data.","The study uses logged replay only and does not alter live traffic.","One bounded system or link class is evaluated.","Privacy and security review is limited but still required."]},"initial_deployment_startup":{"band_2026_usd":"250K_TO_1M","scope":"After favorable replay evidence, engineer and review a capped pilot on selected noncritical links, including integration, monitoring, safeguards, rollback, security, privacy, and evaluation infrastructure.","confidence":"LOW","assumptions":["The existing scheduler supports a reversible integration point.","No hardware replacement or protocol-wide standard change is required.","Pilot traffic and duration remain tightly bounded.","Operator engineering and compliance labor are included."]},"operational_launch":{"band_2026_usd":"1M_TO_5M","scope":"Production hardening and controlled multi-link or multi-site launch, including reliability validation, governance of traffic weights, observability, incident response, training, and staged rollout evaluation.","confidence":"LOW","assumptions":["Launch occurs only after replay and capped-pilot success.","Deployment remains within one operator or protocol domain.","Substantial legacy integration is required but no new physical network is built.","Protected service commitments remain unchanged."]},"annual_recurring":{"band_2026_usd":"250K_TO_1M","scope":"Ongoing state-data processing, monitoring, model or policy tuning, audits, incident response, software maintenance, compliance review, and periodic comparison with the baseline.","confidence":"LOW","assumptions":["Operations cover a bounded operator deployment rather than an industry-wide protocol.","Monitoring includes per-class tail latency, reliability, energy, privacy, and minimum-service thresholds.","Material signaling and computation costs are possible but not quantified.","No major recurring spectrum or capacity purchase is included."]}},"research_burden":"HIGH","earliest_credible_horizon":"3_TO_12_MONTHS","pipeline_gates":{"recognizable_externally_supportable_problem":{"status":"YES","reason":"The packet identifies observable intervals where assigned capacity is unused or carries lower-weight traffic while admissible traffic waits, and distinguishes this claimed loss from physical capacity and required protection margins."},"identifiable_adopter_or_authorizer":{"status":"YES","reason":"The network operator or protocol governance body controlling scheduling is explicitly identified as the decision authority."},"distinct_testable_incremental_claim":{"status":"YES","reason":"The proposal claims improvement over a static scheduler under identical traffic and channel conditions and unchanged power, error, privacy, fairness, latency, and minimum-service limits; no novelty claim is required for this comparison."},"bounded_next_evidence_step":{"status":"YES","reason":"A time-limited logged replay on selected noncritical links can compare the adaptive and static schedulers without exposing live traffic, using explicit problem and intervention falsifiers."},"no_unresolved_safety_or_authority_stop":{"status":"UNCERTAIN","reason":"The packet supplies hard constraints, exclusions, monitoring, and rollback, but external confirmation is still needed that the operator may use the proposed traffic weights and channel-state data without violating privacy or affected-party commitments."},"implementation_cost_scope_and_range":{"status":"UNCERTAIN","reason":"The candidate bounds the technical experiment but provides no system architecture, trace availability, integration complexity, compliance requirements, or resource evidence sufficient to validate even the broad cost bands."}},"blocking_evidence":["Representative traces must show that apparent idle intervals are feasible transmission opportunities rather than required redundancy, guard time, coding overhead, uncertainty margin, synchronization, privacy protection, fairness reservation, or power compliance.","The static baseline must be shown to fall measurably inside the feasible weighted-rate frontier under declared uncertainty bounds.","Under identical replay conditions, the adaptive scheduler must robustly improve preregistered useful-throughput, outage, or delay metrics without crossing any protected-flow, error, privacy, energy, fairness, or tail-latency threshold.","The legitimacy, stability, and non-gameability of traffic weights and minimum-service rules must be established by the relevant authority and affected-party process.","A bounded prior-art review must determine whether the proposed mechanism composition offers a distinguishable contribution relative to existing adaptive scheduling and network-utility approaches.","Trace access, scheduler integration points, monitoring coverage, and rollback latency must be confirmed before credible deployment costs can be assessed."],"next_evidence_step":"With one operator partner, run an offline, time-bounded replay of representative traces from selected noncritical links. Preregister useful reliable throughput, outage, delay tails, energy, error, privacy, and per-class minimum-service thresholds; compare the static scheduler with the proposed adaptive scheduler under identical traffic, channel conditions, and hard constraints. Reject the problem diagnosis if the baseline is already on the feasible weighted-rate frontier or apparent slack is protection-required, and reject the intervention if gains are not robust or any protected threshold is breached.","research_questions":["How often and at what operational scale do representative traces contain genuinely feasible stranded transmission opportunities?","Which apparent idle intervals are required for reliability, synchronization, coding, privacy, fairness, uncertainty, or power compliance?","Is the static baseline inside the feasible weighted-rate frontier after channel-estimation uncertainty and control overhead are included?","Does adaptive allocation improve preregistered outcomes across representative regimes rather than only selected favorable traces?","What signaling, computation, energy, privacy, and oscillation costs arise from acquiring and acting on current state?","Do weak-channel, low-volume, latency-sensitive, and reliability-sensitive flows remain above declared minima, including in tail outcomes?","Who has legitimate authority to define traffic weights, and how will priority inflation or strategic classification be prevented?","What existing adaptive-scheduling or network-utility approaches constitute the nearest prior-art comparator?","What integration, monitoring, compliance, and rollback resources are required in the target network?"] ,"recommendation":"PARTNERED_RESEARCH","uncertainty_constraints":["Problem prevalence and aggregate impact are unsupported by the sealed packet.","Stakeholder demand and willingness to adopt are unmeasured.","World novelty and distinctiveness are unmeasured because prior art is explicitly unsearched.","The claimed gains remain hypotheses until tested on representative traces with a common-condition comparator.","The legitimacy of traffic-value weights and authority over affected service commitments require external confirmation.","Cost bands are resource-equivalent planning ranges based on assumed bounded scope, not observed implementation costs.","Scalability across network architectures, traffic regimes, and governance domains is unknown."],"closed_book_prior_art_boundary":"This assessment makes no claim that adaptive channel allocation, queue-aware scheduling, congestion shadow prices, safeguarded optimization, or their composition is novel, rare, or absent from deployed systems. Prior-art status remains UNSEARCHED; only the candidate's internal mechanism, falsifiability, authority structure, and bounded evidence design are assessed."}