{"id":"W7133283808","doi":"","title":"Maritimes Snow Crab assessment for 2024","year":2025,"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":"Fishing; Snow; Habitat; Stock (firearms); Climate change","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0002048152,0.0002594314,0.00009011345,0.0005913306,0.0002955688,0.0004454971,0.0002686139,0.0002082096,0.01557437],"category_scores_gemma":[0.0005011599,0.00009740319,0.0005132469,0.000370748,0.00008171928,0.0002169818,0.0004656996,0.0002516139,0.002934851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008963191,"about_ca_system_score_gemma":0.000960962,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08334287,"about_ca_topic_score_gemma":0.1773018,"domain_scores_codex":[0.9999154,0.000007533607,0.000004904465,0.00000928818,0.00004555807,0.00001734503],"domain_scores_gemma":[0.9997841,0.000008632985,0.00004283449,0.000007893874,0.0001199094,0.00003678343],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007311145,0.0001054496,0.6684099,0.0005765515,0.000291581,0.00151543,0.0007871009,0.02926845,0.00552781,0.00557235,0.1550908,0.1321235],"study_design_scores_gemma":[0.000035911,0.000271743,0.6428823,0.0003538998,0.00007416894,0.0004508592,0.001162346,0.02509808,0.001941515,0.001634215,0.3260434,0.00005155368],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6688808,0.001209142,0.003943571,0.001543298,0.0003740721,0.000226669,0.07536575,0.000831123,0.2476256],"genre_scores_gemma":[0.8675547,0.0007567793,0.003417873,0.0002706335,0.00005430405,0.0001138107,0.03822564,0.0001439372,0.08946222],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9166571,"threshold_uncertainty_score":0.1657155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008317230678896692,"score_gpt":0.2633205185486975,"score_spread":0.2550032878698008,"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."}}