{"id":"W3007671218","doi":"","title":"The use and value of opportunistic sightings for cetacean conservation and management in Canada","year":2019,"lang":"en","type":"article","venue":"","topic":"Marine animal studies overview","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Fishery; Value (mathematics); Geography; Business; Statistics; Mathematics; Biology","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":[0.001643452,0.0002156136,0.0001933802,0.003390731,0.001641613,0.00256783,0.0008171779,0.0004947992,0.001305573],"category_scores_gemma":[0.00380199,0.0002033607,0.0002977889,0.006889517,0.001548911,0.0006273827,0.0007266804,0.0006719723,0.0000735879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0286486,"about_ca_system_score_gemma":0.04565419,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9949935,"about_ca_topic_score_gemma":0.9987821,"domain_scores_codex":[0.9986604,0.0001649453,0.00006618416,0.000117324,0.0007063789,0.0002847883],"domain_scores_gemma":[0.99375,0.0009446013,0.0007499647,0.00009189018,0.00355679,0.0009066563],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002431634,0.00008434708,0.563026,0.001490044,0.000311717,0.000407065,0.005787829,0.000943567,0.001152693,0.002081639,0.01302032,0.4114516],"study_design_scores_gemma":[0.000007747332,0.00005781597,0.9594279,0.0009423147,0.0001108711,0.0001651853,0.00682894,0.000369646,0.0002642721,0.0002029602,0.03158877,0.00003345608],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.834501,0.1118723,0.0005276125,0.01448373,0.0002690751,0.00006669623,0.005482765,0.00004808515,0.03274871],"genre_scores_gemma":[0.9238208,0.06690239,0.0009545162,0.001199825,0.00007954025,0.0000152255,0.001083052,0.00001642408,0.00592814],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0286486,"threshold_uncertainty_score":0.2078611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0312045533582898,"score_gpt":0.2124222485448431,"score_spread":0.1812176951865533,"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."}}