{"id":"W7128660849","doi":"","title":"Abundance indices update for striped red mullet from professional fishing data for Subareas 7 and 8","year":2024,"lang":"en","type":"report","venue":"Archimer (Ifremer)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Cluster (spacecraft); Fishing; Abundance (ecology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001609232,0.0005731133,0.0003357294,0.003105781,0.0002913112,0.000990876,0.0008579674,0.0002905598,0.02032647],"category_scores_gemma":[0.003501495,0.0003899535,0.0005166109,0.002720071,0.0001376741,0.0009590933,0.001068971,0.0008220373,0.02026218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007608442,"about_ca_system_score_gemma":0.001683882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05109718,"about_ca_topic_score_gemma":0.07915986,"domain_scores_codex":[0.9987734,0.00008670097,0.0001299748,0.0001795862,0.0007226765,0.000107561],"domain_scores_gemma":[0.9968021,0.0001884766,0.0004110207,0.0006752316,0.001795739,0.000127426],"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":[0.0002444539,0.0001617558,0.07048632,0.0005546642,0.0001511493,0.0002315172,0.0007783563,0.00289078,0.006727799,0.00416043,0.6487978,0.264815],"study_design_scores_gemma":[0.00002081784,0.00006433115,0.1374423,0.0001728738,0.00003275339,0.0001480367,0.0003710389,0.00207946,0.002778388,0.0006286352,0.8562217,0.00003971386],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.05699421,0.0005710866,0.02808594,0.0004991373,0.0007571667,0.0005419836,0.8021248,0.004242084,0.1061836],"genre_scores_gemma":[0.04288595,0.0004291525,0.05752635,0.0001340757,0.00009709328,0.0006205859,0.847207,0.001602162,0.04949771],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05109718,"threshold_uncertainty_score":0.1015995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1377822211208881,"score_gpt":0.3932044154592053,"score_spread":0.2554221943383173,"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."}}