{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001037999,0.001042885,0.0007039447,0.002856209,0.000717258,0.00148892,0.0013828,0.0009589082,0.01936526],"category_scores_gemma":[0.003177506,0.0003820043,0.000698486,0.004533141,0.0002107221,0.000782784,0.00150113,0.0007156763,0.02165183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001493025,"about_ca_system_score_gemma":0.0019721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1556448,"about_ca_topic_score_gemma":0.2831422,"domain_scores_codex":[0.9990777,0.0001273511,0.0001434772,0.0003269395,0.0001860132,0.0001384135],"domain_scores_gemma":[0.9981287,0.0001993034,0.0003655347,0.0004183768,0.0007072248,0.0001807937],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0002475423,0.00003963416,0.0296644,0.0007912362,0.0001197091,0.0001106975,0.0001304602,0.0004742672,0.0005700637,0.0005809054,0.9531748,0.01409629],"study_design_scores_gemma":[0.0001398602,0.00004038851,0.1074171,0.0007193423,0.00007780924,0.0001296637,0.000314194,0.0008631869,0.0006291172,0.0005596349,0.8890436,0.00006617825],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002201495,0.0001310668,0.00008638874,0.00007095464,0.00002087342,0.00001654242,0.9953902,0.0001462257,0.001936257],"genre_scores_gemma":[0.00231385,0.00007017258,0.0004067761,0.00004355249,0.000006350871,0.00007755272,0.9953877,0.00004047949,0.001653598],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1556448,"threshold_uncertainty_score":0.3094776,"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."}}