{"id":"W4253811847","doi":"10.1121/10.0000671.2","title":"10.1121/10.0000671.2","year":2020,"lang":"en","type":"dataset","venue":"Default Digital Object Group","topic":"Animal Vocal Communication and Behavior","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; University of Windsor","funders":"","keywords":"Context (archaeology); Biology; Vocal communication; Sequence (biology); Set (abstract data type); Evolutionary biology; Communication; Speech recognition; Psychology; Computer science; Paleontology; Genetics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0000743815,0.0004811884,0.0003916503,0.00006279255,0.0001113649,0.0002677476,0.001057105,0.0005905363,0.001990336],"category_scores_gemma":[0.0002640984,0.0004606492,0.0003541507,0.0001718936,0.0001553849,0.00001399248,0.0008109558,0.0003972463,0.01389553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003007416,"about_ca_system_score_gemma":0.0001045814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002642787,"about_ca_topic_score_gemma":0.00004380685,"domain_scores_codex":[0.9981502,0.00006195456,0.0004158085,0.000685423,0.0003103641,0.000376191],"domain_scores_gemma":[0.9982522,0.00002681104,0.0002035246,0.001156091,0.0001072514,0.0002541656],"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":[0.0001986477,0.0001858584,0.000006555435,0.00004066726,0.0000625103,0.00002157445,0.000002672864,2.42777e-7,0.001301778,0.000003424007,0.9949204,0.003255703],"study_design_scores_gemma":[0.0003632702,0.001004393,0.00008644404,0.00002534094,0.00006531511,0.00002354691,0.00002084371,0.000001779868,0.0004908334,0.000006525299,0.9973459,0.0005658063],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000352088,0.0004578777,0.00002159148,0.00007959015,0.0001041744,0.0002739746,0.9907746,0.00005568203,0.007880386],"genre_scores_gemma":[0.008041417,0.0001587954,0.00003578789,0.0006394928,0.00044426,0.00005990837,0.9792627,0.00005708418,0.01130055],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01190519,"threshold_uncertainty_score":0.9997845,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0180903924002201,"score_gpt":0.2715581817431741,"score_spread":0.253467789342954,"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."}}