{"id":"W6921750024","doi":"10.7944/00rk-3q93","title":"Yukon River Inconnu biometric data","year":2024,"lang":"en","type":"dataset","venue":"FWS DOI Tool Production Environment","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Tributary; Biometrics; Data set; Identification (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":[0.0004423859,0.0007952763,0.000901479,0.002019394,0.0008875419,0.0009706471,0.001419547,0.0009446812,0.02013002],"category_scores_gemma":[0.002020881,0.0003290498,0.0004623997,0.005058472,0.0003586138,0.0004827075,0.001078769,0.0006071065,0.01771301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00119101,"about_ca_system_score_gemma":0.003113303,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1761272,"about_ca_topic_score_gemma":0.3009959,"domain_scores_codex":[0.9994266,0.00005945109,0.00007558015,0.0001835938,0.0001351663,0.000119618],"domain_scores_gemma":[0.9988556,0.0001091239,0.00009165645,0.0002176715,0.0006388825,0.00008704963],"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":[0.0001848139,0.00008241318,0.02567308,0.0006127948,0.00008931825,0.0001864116,0.000186427,0.001077721,0.0004304725,0.001235368,0.9602541,0.009987109],"study_design_scores_gemma":[0.0001287688,0.00003549259,0.0933488,0.0003052735,0.0000803425,0.0002059985,0.0007334062,0.001351453,0.0005546567,0.0008308021,0.9023508,0.00007421034],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002793518,0.00006759599,0.00007189149,0.00003168556,0.00001912186,0.00001712317,0.995886,0.0001289354,0.0009840352],"genre_scores_gemma":[0.00306498,0.00002973559,0.0001826748,0.0000191905,0.000002386679,0.00005485802,0.9956896,0.00001682376,0.0009397968],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8238729,"threshold_uncertainty_score":0.3502039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06872708729749896,"score_gpt":0.2205408101653631,"score_spread":0.1518137228678641,"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."}}