{"id":"W6950401773","doi":"10.5683/sp3/lfnpeq","title":"Killer Whale 3D Model","year":2024,"lang":"en","type":"dataset","venue":"Borealis","topic":"Oceanographic and Atmospheric Processes","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; National Research Council Canada; McGill University","funders":"","keywords":"Whale; Mobile device; Event (particle physics); Lidar; Pregnancy","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":[0.0004333104,0.0021164,0.001052103,0.001613408,0.0006285,0.001157962,0.002793416,0.001465335,0.0336931],"category_scores_gemma":[0.001252785,0.0005629411,0.001820358,0.001923118,0.0003915323,0.0008257362,0.001603049,0.001551799,0.05101129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005540572,"about_ca_system_score_gemma":0.0008398864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04139385,"about_ca_topic_score_gemma":0.1141138,"domain_scores_codex":[0.999613,0.00003980464,0.00002712423,0.0001305849,0.0001141331,0.00007531081],"domain_scores_gemma":[0.9996958,0.00003870631,0.00001580816,0.00009439489,0.000120386,0.00003494267],"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":[0.0002434396,0.0001158105,0.005731325,0.0005267126,0.0001219758,0.0001924029,0.0001108914,0.005189233,0.001316084,0.0009830351,0.966408,0.01906105],"study_design_scores_gemma":[0.0002125875,0.000085771,0.01161838,0.0002369856,0.00007965299,0.0003808264,0.0003637778,0.01438327,0.001842478,0.001723645,0.968994,0.00007865702],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004044175,0.0002907264,0.001847004,0.0001637361,0.0001639291,0.00007059863,0.9864197,0.003276746,0.003723323],"genre_scores_gemma":[0.004298537,0.00009234341,0.002142889,0.00004239457,0.000009092011,0.0001059705,0.9914404,0.0001568374,0.001711451],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04139385,"threshold_uncertainty_score":0.1127146,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01257838112814111,"score_gpt":0.2184753363467973,"score_spread":0.2058969552186562,"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."}}