{"id":"W7133277689","doi":"","title":"Green Sea Urchin stock status update and harvest options","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":"Stock assessment; Stock (firearms); Fish stock; Sea urchin; Population; Fisheries management; Sustainable 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":[0.002097491,0.0004128631,0.0002423641,0.003563703,0.0007315268,0.001415955,0.0009632109,0.000616072,0.01122588],"category_scores_gemma":[0.004644841,0.0002107659,0.0003703774,0.002504384,0.0001510347,0.0009086836,0.0006885047,0.0006846645,0.002584207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003314689,"about_ca_system_score_gemma":0.003777504,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5094569,"about_ca_topic_score_gemma":0.723849,"domain_scores_codex":[0.9990754,0.00005829961,0.0001016351,0.00005186491,0.0006021386,0.0001107023],"domain_scores_gemma":[0.9947469,0.0002137753,0.0003577134,0.0001796193,0.004093983,0.0004079932],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003087993,0.0002039085,0.2190074,0.0003213639,0.00008112197,0.000350131,0.0004980767,0.003352066,0.0009525276,0.001585642,0.3678987,0.4054403],"study_design_scores_gemma":[0.00004683787,0.0001105153,0.4404773,0.0006408541,0.00009397967,0.0002207304,0.00100064,0.003747275,0.001061201,0.001004173,0.5515068,0.00008965575],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3622299,0.009527306,0.00591137,0.01445338,0.001269882,0.001293488,0.2846369,0.002700019,0.3179777],"genre_scores_gemma":[0.4990462,0.01031869,0.02544446,0.003347527,0.0002626654,0.0009155777,0.2702949,0.0003287345,0.1900412],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4905431,"threshold_uncertainty_score":0.9868641,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008446949026766012,"score_gpt":0.2395988878587946,"score_spread":0.2311519388320286,"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."}}