{"id":"W7104026489","doi":"10.14286/5evyzo","title":"Gulf of St. Lawrence Herring","year":2021,"lang":"en","type":"dataset","venue":"Open MIND","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ocean Tracking Network","funders":"","keywords":"Herring; Stock assessment; Pelagic zone; Stock (firearms); Fishing; Fish stock; Fisheries management; Satellite tracking","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007291728,0.0007160689,0.0004023381,0.002795711,0.001325868,0.001767767,0.0009197004,0.0003436679,0.05241922],"category_scores_gemma":[0.001483667,0.0003025202,0.0003180729,0.00341656,0.0001980622,0.000755406,0.0009211506,0.0004849884,0.04012095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00350397,"about_ca_system_score_gemma":0.005624515,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5435858,"about_ca_topic_score_gemma":0.7510653,"domain_scores_codex":[0.999175,0.00003397029,0.00006704106,0.0001713783,0.0004355547,0.0001169269],"domain_scores_gemma":[0.9983606,0.00003554108,0.0001320123,0.0001367792,0.001230482,0.0001046011],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001663889,0.00006336103,0.0495613,0.0002409782,0.00004872962,0.0001202197,0.0002344911,0.000161313,0.0006307132,0.001614335,0.870237,0.07692115],"study_design_scores_gemma":[0.00002677367,0.00004541741,0.1356396,0.0002232864,0.00003366116,0.00009028198,0.0004525759,0.0002979696,0.0005733034,0.000272049,0.8623086,0.00003642215],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.03099032,0.0007314062,0.0009956395,0.0006306844,0.0005094777,0.000277953,0.7618303,0.001276377,0.2027579],"genre_scores_gemma":[0.04152342,0.001138801,0.0037624,0.0005253919,0.00006834875,0.0002409132,0.7672876,0.0003094984,0.1851437],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4564142,"threshold_uncertainty_score":0.9182042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06607652281617202,"score_gpt":0.3501322995503489,"score_spread":0.2840557767341768,"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."}}