{"id":"W7133278878","doi":"","title":"Réponse des Sciences : Mise à jour des indicateurs de l’état des stocks de homard de la Côte-Nord (ZPH 15, 16 et 18) et de l’île d’Anticosti (ZPH 17)","year":2022,"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":"Flood myth; Human science; Stock (firearms); European union","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":[0.005148442,0.0005767412,0.0005790038,0.004459162,0.002443616,0.004217666,0.001009121,0.0008259336,0.009787979],"category_scores_gemma":[0.008219802,0.0002656466,0.0006935747,0.004997978,0.000909656,0.0009233856,0.001183624,0.0008695837,0.00231423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02418352,"about_ca_system_score_gemma":0.04119916,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.946769,"about_ca_topic_score_gemma":0.9782872,"domain_scores_codex":[0.9978001,0.0002636747,0.00008319457,0.000328537,0.001245775,0.0002788951],"domain_scores_gemma":[0.9820931,0.0009557699,0.001325961,0.000582763,0.01394055,0.001101837],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001262725,0.0001019103,0.6595384,0.001768932,0.0010161,0.000667169,0.005743723,0.003555019,0.01619142,0.004703777,0.06319328,0.2422575],"study_design_scores_gemma":[0.00002304203,0.0001344769,0.903514,0.0004119999,0.000136722,0.00005054849,0.002977007,0.001044036,0.004286023,0.0006014336,0.08675068,0.00006995437],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6557836,0.0244885,0.01192815,0.01750736,0.001713534,0.00066978,0.1021641,0.001420466,0.1843245],"genre_scores_gemma":[0.8016873,0.007602555,0.01452732,0.002055558,0.0002420154,0.0002591825,0.02801914,0.0003223834,0.1452846],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.053231,"threshold_uncertainty_score":0.1754645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02091361387011839,"score_gpt":0.2876325909759415,"score_spread":0.2667189771058232,"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."}}