{"id":"W6948327460","doi":"10.5061/dryad.brv15dv8b","title":"Automated classification of avian vocal activity using acoustic indices in regional and heterogeneous datasets","year":2020,"lang":"en","type":"dataset","venue":"DRYAD","topic":"Orthoptera Research and Taxonomy","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Environment and Climate Change Canada","funders":"","keywords":"Data collection; Cluster analysis; Sample (material); Identification (biology); Variation (astronomy); Process (computing); Regression analysis; Data processing","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001170004,0.0001482613,0.0002413708,0.00003490708,0.00006586222,0.00004907666,0.000220266,0.0001809591,0.00006292312],"category_scores_gemma":[0.00005129906,0.00006747249,0.00003918946,0.0002251494,0.0001120918,0.00009834592,0.0001332817,0.0002383658,0.00001558044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002953457,"about_ca_system_score_gemma":0.00003137665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001389773,"about_ca_topic_score_gemma":0.004497867,"domain_scores_codex":[0.9989116,0.0001256229,0.0001901785,0.0003366849,0.0002294537,0.0002064466],"domain_scores_gemma":[0.999479,0.0001296106,0.0001738919,0.00007557125,0.00001960067,0.0001223113],"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":[0.0002862272,0.0004290545,0.005019989,0.0003204833,0.0000720658,0.0001804244,0.00001753462,0.00002598085,0.05782992,0.000001424351,0.8681974,0.06761949],"study_design_scores_gemma":[0.0002791786,0.0003523448,0.1775579,0.0001398367,0.00004054653,0.00003268334,0.0000367783,0.006625001,0.0003148869,0.00001089555,0.8142374,0.0003725706],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.3652161,0.00006494322,3.963454e-7,0.00009726664,0.00002069178,0.0001410681,0.6344419,0.00001603496,0.000001631551],"genre_scores_gemma":[0.3684222,0.0001130078,0.0000167066,0.0000313388,0.00006914538,0.000007125047,0.6313396,4.761739e-7,4.893699e-7],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1725379,"threshold_uncertainty_score":0.2751448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08028647039979231,"score_gpt":0.300606670551007,"score_spread":0.2203202001512147,"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."}}