{"id":"W7133278100","doi":"","title":"Northern Hudson Bay narwhal abundance estimates","year":2022,"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":"Bay; Abundance (ecology); Population; Series (stratigraphy); Population model; Time series; Current (fluid)","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":[0.0006821056,0.0004435212,0.0002954643,0.0009509633,0.0003551378,0.0005400131,0.0009492713,0.0002469947,0.01032549],"category_scores_gemma":[0.00204519,0.0002544068,0.0005137398,0.0008888735,0.0001704551,0.000414869,0.0008722707,0.0003446644,0.00166114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003393394,"about_ca_system_score_gemma":0.002923607,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.612738,"about_ca_topic_score_gemma":0.6832004,"domain_scores_codex":[0.9997427,0.00002610813,0.00001812316,0.00007546869,0.00009836086,0.0000392351],"domain_scores_gemma":[0.9994403,0.00004578371,0.0000678986,0.00003603214,0.0003636366,0.00004640944],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001067606,0.00006985421,0.8436142,0.0002233561,0.0001460706,0.000282766,0.0009130524,0.07257809,0.0009424366,0.002340105,0.03767902,0.04110443],"study_design_scores_gemma":[0.00006745657,0.0001636095,0.6783482,0.000458867,0.0001629715,0.0001665087,0.003659686,0.2188456,0.00112587,0.002621398,0.09426972,0.000110153],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8777233,0.0003921404,0.01832946,0.00060934,0.00009802407,0.0006259216,0.07047767,0.0008745551,0.03086944],"genre_scores_gemma":[0.9129461,0.0004608211,0.01671816,0.0001655615,0.00002241088,0.0006220955,0.03923513,0.0001326144,0.02969717],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.387262,"threshold_uncertainty_score":0.7790853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007628768294929436,"score_gpt":0.2300232386981494,"score_spread":0.22239447040322,"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."}}