{"id":"W6904803885","doi":"10.14286/m8xeat","title":"Mackerel tracking in the Northwest Arm","year":2024,"lang":"en","type":"dataset","venue":"Ocean Tracking Network","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ocean Tracking Network","funders":"","keywords":"Stock (firearms); Track (disk drive); Mackerel; Stock assessment; Fisheries management; Fish stock","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.003599813,0.001446051,0.001219418,0.0006101445,0.0004582815,0.001512956,0.003138766,0.0009783674,0.0004762846],"category_scores_gemma":[0.0002238012,0.001149549,0.0006090556,0.003306312,0.0003023153,0.0003281396,0.0003449232,0.005407321,0.02968017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004565534,"about_ca_system_score_gemma":0.000292492,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007053417,"about_ca_topic_score_gemma":0.01870869,"domain_scores_codex":[0.9922888,0.0007909194,0.001475531,0.001739302,0.00156321,0.002142265],"domain_scores_gemma":[0.9953136,0.001136206,0.0006989361,0.002527131,0.0001197275,0.0002043336],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000062915,0.0003252252,0.001539087,0.0004603919,0.0001871876,0.002462367,0.0003441545,0.00376317,3.238676e-7,0.00009006002,0.9895132,0.001251926],"study_design_scores_gemma":[0.0004249992,0.00009030828,0.003564012,0.002783138,0.0006224584,0.0002719544,0.0001543802,0.0001511526,0.000001012584,0.001194285,0.9895014,0.001240929],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001156993,0.005254857,0.0000020243,0.0002230418,0.003529921,0.001069384,0.9876235,0.0004698354,0.000670407],"genre_scores_gemma":[0.01453393,0.0005758004,0.00007055653,0.0009178468,0.008577892,0.00004353024,0.9746513,0.0005481958,0.00008099302],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02920389,"threshold_uncertainty_score":0.9998289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02523218986052348,"score_gpt":0.2859636589503857,"score_spread":0.2607314690898622,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}