{"id":"W4401900528","doi":"10.1101/2024.08.26.609387","title":"YOLO-Behaviour: A simple, flexible framework to automatically quantify animal behaviours from videos","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Bat Biology and Ecology Studies","field":"Agricultural and Biological Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Simple (philosophy); Computer science; Animal behavior; Computer vision; Artificial intelligence; Human–computer interaction; Biology; Zoology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001730116,0.00190248,0.0009227787,0.002767305,0.0004478059,0.001402884,0.002472256,0.001334529,0.004227003],"category_scores_gemma":[0.005804067,0.0008191001,0.00179543,0.0005662574,0.0007359344,0.001447055,0.00226955,0.001289055,0.002757101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009300342,"about_ca_system_score_gemma":0.001357479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01698842,"about_ca_topic_score_gemma":0.03913852,"domain_scores_codex":[0.999156,0.0001344743,0.00005483303,0.0003878887,0.0001818554,0.00008497268],"domain_scores_gemma":[0.999014,0.0003656536,0.0001546118,0.0001439884,0.0002092702,0.000112445],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00106888,0.0005721043,0.02703266,0.002387121,0.0007949232,0.0005762709,0.001285341,0.08543403,0.08701596,0.01195668,0.07854084,0.7033352],"study_design_scores_gemma":[0.00008020736,0.000205992,0.01681189,0.0003186436,0.000111933,0.0003333843,0.0002122085,0.9095971,0.02009077,0.0160684,0.03596064,0.0002088402],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009187127,0.0004189753,0.8885435,0.000215218,0.00008008968,0.0005126735,0.004304742,0.0953021,0.001435584],"genre_scores_gemma":[0.1129114,0.0004290425,0.8648663,0.0004511037,0.00006349705,0.001471348,0.01142724,0.004924589,0.003455567],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01698842,"threshold_uncertainty_score":0.03377908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02455257566362638,"score_gpt":0.2525525982405636,"score_spread":0.2280000225769372,"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."}}