{"id":"W3206959221","doi":"10.1101/2021.10.20.464614","title":"Markerless mouse tracking for social experiments","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Animal Behavior and Welfare Studies","field":"Veterinary","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Children's Hospital; Hotchkiss Brain Institute; University of Calgary","funders":"","keywords":"Snout; Tracking (education); Identifier; Computer science; Computer vision; Artificial intelligence; Eye tracking; Pattern recognition (psychology); Psychology; Biology; Anatomy","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":[0.001173342,0.0006600089,0.0005260326,0.0005632518,0.0002060514,0.0004722614,0.001240781,0.001031916,0.003030836],"category_scores_gemma":[0.001971418,0.0003173916,0.0003882552,0.0002786578,0.0005194175,0.0006467217,0.0008810708,0.0007940158,0.001011644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003619004,"about_ca_system_score_gemma":0.0003954973,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005582697,"about_ca_topic_score_gemma":0.0007573878,"domain_scores_codex":[0.9994503,0.0001355819,0.00002891181,0.0001921947,0.000142784,0.00005028312],"domain_scores_gemma":[0.9988966,0.0002886901,0.000301737,0.0002799992,0.0001357897,0.00009720474],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003208003,0.0000976447,0.001590579,0.0002958185,0.00006834853,0.0001359263,0.00006923299,0.007373723,0.8870487,0.001869512,0.001931297,0.09919844],"study_design_scores_gemma":[0.000123203,0.00118327,0.01473401,0.0001331811,0.0001011116,0.0008738024,0.0000597303,0.3050899,0.6456176,0.006995045,0.02498916,0.00009993923],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04851926,0.0005178077,0.9446821,0.0001446859,0.0001413348,0.0001192913,0.0005868755,0.003965174,0.001323551],"genre_scores_gemma":[0.3993274,0.0007551672,0.5942158,0.0002821161,0.00008320124,0.0008607876,0.001077533,0.0003683801,0.003029539],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003030836,"threshold_uncertainty_score":0.01013917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08017026230743524,"score_gpt":0.3239403484337585,"score_spread":0.2437700861263233,"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."}}