{"id":"W7133268286","doi":"","title":"Analyses des prises accessoires de la pêche côtière du homard dans les ZPH 27, 31A, 31B, 33, 34 et 35","year":2023,"lang":"fr","type":"other","venue":"Federal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agricultural development; Context (archaeology); Independence (probability theory)","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":[0.006969252,0.0007434375,0.000979654,0.003264365,0.002391123,0.002127988,0.00160667,0.001122412,0.008831179],"category_scores_gemma":[0.01566023,0.0005584634,0.00132432,0.004625477,0.001280727,0.001029033,0.001899778,0.001429574,0.001250555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006225934,"about_ca_system_score_gemma":0.01577313,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4303506,"about_ca_topic_score_gemma":0.5435424,"domain_scores_codex":[0.9939243,0.001741725,0.0005042343,0.0009922161,0.001926841,0.0009106155],"domain_scores_gemma":[0.9892548,0.002034382,0.001315615,0.0007396034,0.005991479,0.0006640464],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001453892,0.0002463119,0.79886,0.002928083,0.0009218653,0.0008943526,0.02090822,0.001175427,0.002769426,0.006093655,0.02366779,0.140081],"study_design_scores_gemma":[0.00004908551,0.000297754,0.9162636,0.001174328,0.0003626039,0.0002127883,0.0117331,0.000684716,0.001509624,0.0007601831,0.06688493,0.00006729623],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8747661,0.01092998,0.02169436,0.00319531,0.0005543591,0.003453091,0.05050882,0.0003315689,0.03456639],"genre_scores_gemma":[0.8816372,0.005262467,0.02974368,0.001720709,0.0001411867,0.007816728,0.02915619,0.0002377924,0.04428414],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5696494,"threshold_uncertainty_score":0.8556914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02392221491603494,"score_gpt":0.2994308194440229,"score_spread":0.2755086045279879,"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."}}