{"closest_prior_art":[{"name":"Amazon SQS queue-health monitoring with CloudWatch","overlap":"Maintains backlog-level and oldest-item-age metrics, detects processing bottlenecks, supports threshold alarms, relates backlog to processing capacity, and separately monitors dead-letter queues so failed items are not mistaken for completed work.","remaining_difference":"It is generic message-queue practice, not an athlete-session governance workflow. It does not provide the proposal's exact receipt-to-publication unit, daily immutable-event reconciliation, reason-coded validation outcomes, clearance-day bands, or shadow simulation of authorized analyst routing.","source_ids":["SRC3"]},{"name":"Catapult OpenField missing-activity-data controls","overlap":"Directly addresses athlete-session data that are unavailable because files were not fully synchronized, warns users when activity data are incomplete, requires associated athlete data for accurate reprocessing and reporting, and documents recovery through synchronization across machines or sub-users.","remaining_difference":"The product guidance treats individual missing-upload incidents. It does not expose a reconciled stock of all unresolved records, oldest-record and clearance-capacity thresholds, residual accounting, coupled exception stocks, or sustainable backlog-control experiments.","source_ids":["SRC2"]},{"name":"Missing-data analysis for sport-science wearable dashboards","overlap":"Shows that wearable data can be absent for training sessions, that sport dashboards may conceal consequential missingness, and that incomplete displays can bias performance or health decisions.","remaining_difference":"The research focuses on statistical missingness and imputation after data are absent, rather than operational control of uploaded-but-unvalidated records through stock-flow reconciliation, age-prioritized clearance, capacity routing and anti-displacement checks.","source_ids":["SRC1"]}],"contrastive_claim_falsifier":"The contrastive claim is falsified if the 28-day reconstruction finds no decision-window carryover, or if replaying level-, age- and exception-stock alerts produces no distinguishable improvement in projected closing stock or oldest-record age over the existing workflow after all transfers, rejections, deletions and residuals are reconciled. It is also falsified if ordinary upload/completion monitoring already supplies equivalent reconciled level governance.","contrastive_claim_remaining":"Within sport-science wearable workflows, a reconciled level-and-age control layer may add operational value beyond missing-data warnings, rate dashboards and generic utilization measures when it reduces decision-relevant carryover without relaxing validation or displacing unresolved records into exception queues.","experiment_id":"eoa_inverse_innovation_exp13_second_slot_policy60_20260806","gates":{"adequate_source_search":{"rationale":"The bounded search covered the proposal directly, missing-data and synchronization terminology, athlete-monitoring products and governance guidance, and the component combination of backlog depth, oldest-item age, throughput alarms and dead-letter handling. Four opened sources span four publishers and include research, first-party documentation and official guidance. No full sport-specific implementation was found, but this is sufficient for a coarse screen rather than a novelty determination.","source_ids":["SRC1","SRC2","SRC3","SRC4"],"status":"PASS"},"bounded_next_test":{"rationale":"A 28-day, one-squad retrospective reconstruction using already authorized audit logs is finite, read-only and capable of measuring carryover, age, residuals, exception displacement and replayed alerts against the documented baseline. Catapult's synchronization failure modes and established queue-health metrics make the proposed observables technically plausible, although local log completeness remains to be tested.","source_ids":["SRC2","SRC3"],"status":"PASS"},"distinct_testable_claim":{"rationale":"The remaining claim is narrower than the located work: a sport-specific, reconciled stock-and-age controller should outperform rate-only or incident-only monitoring without hidden transfers or weaker validation. Daily closing stock and oldest-record age provide falsifiable outcomes.","source_ids":["SRC1","SRC2","SRC3"],"status":"PASS"},"no_obvious_safety_or_authority_stop":{"rationale":"The authorized first step is limited to existing data, retrospective reconstruction and shadow-mode routing; it neither changes training nor validation decisions. The designated governance lead controls progression, and the proposal's restrictions and rollback conditions align with official athlete-centric governance principles. Local privacy, access-control and employment rules still require compliance but do not create an obvious categorical stop for the bounded read-only test.","source_ids":["SRC4"],"status":"PASS"},"supported_problem":{"rationale":"Research documents missing wearable sessions and biased sport-science dashboards, while Catapult documents concrete incomplete-upload and cross-machine synchronization failures that prevent accurate reprocessing and reporting. These sources make the problem visible, but they do not establish that persistent aging validation backlogs are prevalent or survive into coaching decision windows at a particular unit.","source_ids":["SRC1","SRC2"],"status":"PASS"}},"prior_art_disposition":"ADJACENT_PRIOR_ART","problem_evidence":{"finding":"The general problem is visible: athlete wearable sessions can be missing because of equipment, compliance or synchronization failures, incomplete data can block accurate report processing, and dashboards can obscure decision-relevant missingness. Evidence for the proposal's stronger premise—a persistent stock of uploaded-but-unvalidated records aging across coaching decision windows—is indirect and must be established locally.","source_ids":["SRC1","SRC2"],"status":"PARTLY_SUPPORTED"},"research_id":"eoa_inverse_innovation_exp13_light_screen_20260806","schema_version":1,"screen_id":"E13P060","screen_survival":true,"search_lanes":{"component_combination":{"no_result_note":"No retained source combined exact athlete-session stock-flow reconciliation, residual accounting, age/capacity thresholds and monitoring of every exception stock.","queries":["official queue monitoring backlog oldest message age dead letter queue threshold","site:docs.aws.amazon.com SQS backlog age oldest message dead-letter queue monitoring","data quality backlog reconciliation stock flow records validation queue monitoring standard"],"source_ids":["SRC3"]},"direct_problem_and_intervention":{"no_result_note":"No direct implementation of the complete proposed athlete-session ledger was located.","queries":["unvalidated athlete session data backlog validation dashboard","athlete monitoring data quality missing wearable training session records coaches research","sports science athlete management system data validation workflow wearable upload missing data"],"source_ids":["SRC1","SRC2"]},"products_practices_and_standards":{"no_result_note":null,"queries":["site:support.catapultsports.com data upload session missing athlete validation OpenField","athlete management software data validation workflow session data quality official","Australian Institute of Sport athlete data governance performance data official framework"],"source_ids":["SRC2","SRC4"]},"synonyms_and_historical_terms":{"no_result_note":null,"queries":["wearable sports data late synchronization parser identity mismatch athlete monitoring","sports wearable platform sync upload session data quality check coach dashboard official","athlete data governance wearable monitoring privacy authority coaches performance data official guidance"],"source_ids":["SRC1","SRC2","SRC4"]}},"sources":[{"claims_supported":["Wearable observations are commonly used for athlete performance and health decisions.","Training-session data are commonly missing because of equipment malfunction, athlete non-compliance and other real-world causes.","Sport-science dashboards can conceal missing-data problems and thereby convey biased information."],"publisher":"U.S. National Library of Medicine (PubMed)","source_id":"SRC1","source_type":"PRIMARY_RESEARCH","title":"Missing Data in Sport Science: A Didactic Example Using Wearables in American Football","url":"https://pubmed.ncbi.nlm.nih.gov/37027076/"},{"claims_supported":["Catapult OpenField activities can lack associated athlete data because files were not fully uploaded or synchronized.","Incomplete athlete data prevent accurate cloud reprocessing and reporting and trigger a warning.","Relevant data may remain on another machine or sub-user, illustrating distributed and potentially hidden unresolved records."],"publisher":"Catapult Sports","source_id":"SRC2","source_type":"FIRST_PARTY_PRODUCT","title":"Missing Activity Data - Unable to Edit Activity via Cloud Editor","url":"https://support.catapultsports.com/hc/en-us/articles/10720780566415-Missing-Activity-Data-Unable-to-Edit-Activity-via-Cloud-Editor"},{"claims_supported":["Established queue monitoring uses backlog depth and age of the oldest unprocessed item as distinct health metrics.","Consistently high backlog can indicate under-provisioned consumers or stuck processing, and alarms can be set on backlog growth.","Dead-letter queues require separate monitoring, and raw inflow/outflow counts can misstate state because retries, duplicates and automatic transfers affect metric interpretation."],"publisher":"Amazon Web Services","source_id":"SRC3","source_type":"OFFICIAL_GUIDANCE","title":"Available CloudWatch metrics for Amazon SQS","url":"https://docs.aws.amazon.com/AWSSimpleQueueService/latest/SQSDeveloperGuide/sqs-available-cloudwatch-metrics.html"},{"claims_supported":["High-performance sport organizations should govern technology and athlete information in athletes' best interests.","Athlete information is managed for and on behalf of athletes rather than owned by practitioners or administrators.","The guidance is intended as best practice for the Australian national high-performance sport system."],"publisher":"Australian Sports Commission / Australian Institute of Sport","source_id":"SRC4","source_type":"OFFICIAL_GUIDANCE","title":"Data Governance: Best Practice Principles on Athlete-Centric Governance of Technology and Athlete Information","url":"https://www.ausport.gov.au/ais/performance-support/topicinitiative/data-governance"}],"world_novelty_boundary":"This bounded public-web screen found adjacent practices in sport missing-data handling, first-party synchronization controls, generic queue backlog monitoring and athlete-data governance. It did not establish world novelty, patentability, market size, expert acceptance or realized value, and it cannot exclude unpublished internal workflows, patents, vendor features behind authentication, non-English material or differently described implementations."}