{"id":"W4402475286","doi":"10.1109/jsen.2024.3454544","title":"Transformer-Based Dog Behavior Classification With Motion Sensors","year":2024,"lang":"en","type":"article","venue":"IEEE Sensors Journal","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Transformer; Computer science; Artificial intelligence; Electrical engineering; Engineering; Voltage","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":[],"consensus_categories":[],"category_scores_codex":[0.0009998946,0.0001956428,0.0001854602,0.0003075864,0.0002365863,0.0006591011,0.0003348872,0.0000949997,0.0000268153],"category_scores_gemma":[0.00001781913,0.0001466766,0.0001468689,0.0005989741,0.00006031516,0.0006655219,0.000003914086,0.0005334548,0.00007461914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009866925,"about_ca_system_score_gemma":0.0001669997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006495666,"about_ca_topic_score_gemma":0.000006191283,"domain_scores_codex":[0.9981544,0.0002754971,0.0003344273,0.0003673901,0.0005164802,0.0003518079],"domain_scores_gemma":[0.9991102,0.0001524786,0.00009620556,0.0003188127,0.0001590434,0.0001632517],"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":[0.00009529684,0.0004133184,0.01087124,0.0001623968,0.0001963309,0.00285077,0.002473884,0.02739341,0.09667028,0.003716781,0.00205445,0.8531018],"study_design_scores_gemma":[0.00285071,0.001261575,0.1774201,0.0008200217,0.0002868202,0.01032393,0.0002764623,0.6112989,0.1702456,0.002230246,0.02114958,0.001836043],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3820164,0.00008734623,0.6145964,0.001262496,0.001218658,0.0001096205,0.000002934943,0.0002158409,0.0004903047],"genre_scores_gemma":[0.9565364,0.00003862101,0.04279416,0.00008748646,0.0003344533,0.000008012389,0.00000184844,0.00002546227,0.0001735924],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8512658,"threshold_uncertainty_score":0.6355727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04166590432061326,"score_gpt":0.3158318087162726,"score_spread":0.2741659043956594,"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."}}