{"id":"W7133272837","doi":"","title":"Science response: Stock status update of Scotian Shelf snow crab","year":2022,"lang":"en","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":"Fisheries and Oceans Canada","keywords":"Stock assessment; Stock (firearms); Snow; Fish stock; Ecosystem; Fisheries management","routes":{"ca_aff":false,"ca_fund":true,"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":[0.002375208,0.0004499429,0.0003546276,0.00261737,0.0009136217,0.001152707,0.0009119348,0.001846257,0.0319057],"category_scores_gemma":[0.007379963,0.000280862,0.0003765325,0.00205335,0.0002377035,0.0005577658,0.001014351,0.001099824,0.02255542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003129646,"about_ca_system_score_gemma":0.01056444,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3517161,"about_ca_topic_score_gemma":0.4171025,"domain_scores_codex":[0.9981734,0.0001077642,0.0001380298,0.00009066308,0.00128756,0.0002025819],"domain_scores_gemma":[0.9784192,0.0008140268,0.00101687,0.0006067806,0.01796335,0.001179848],"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":[0.00006058655,0.00002672486,0.003866148,0.0001349921,0.000004589887,0.00006989515,0.00004023847,0.00009335778,0.0003767701,0.0001165697,0.977763,0.01744712],"study_design_scores_gemma":[0.00002559834,0.00005839915,0.03271428,0.0001263924,0.00001029391,0.00004451212,0.0001816982,0.000225133,0.0004725117,0.00009155166,0.966029,0.00002053736],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.03547623,0.004457678,0.002847788,0.106095,0.03457011,0.003826244,0.4310538,0.004408583,0.3772646],"genre_scores_gemma":[0.06481005,0.003793973,0.006257823,0.03302478,0.004409277,0.001854336,0.2317043,0.0005526993,0.6535928],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6482839,"threshold_uncertainty_score":0.6993378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008435073002428689,"score_gpt":0.2419501126862477,"score_spread":0.233515039683819,"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."}}