{"id":"W4294891768","doi":"10.1145/3552312","title":"BodyTrak","year":2022,"lang":"en","type":"article","venue":"Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Torso; Computer vision; Artificial intelligence; Computer science; RGB color model; Sitting; Pose; Computer graphics (images); Medicine; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001614449,0.0001224618,0.0001523455,0.0001852842,0.000429556,0.00008537072,0.002134315,0.00004458346,0.00002557161],"category_scores_gemma":[0.0002650197,0.00009093559,0.00006946761,0.0003751011,0.0001050921,0.0004290917,0.003016294,0.0004331282,0.000006569455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006019708,"about_ca_system_score_gemma":0.00001501329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000971495,"about_ca_topic_score_gemma":4.83218e-7,"domain_scores_codex":[0.9990863,0.000008867935,0.0001677701,0.0003143455,0.0002374064,0.000185311],"domain_scores_gemma":[0.9991808,0.00009108464,0.0002127065,0.0003957112,0.0001051814,0.00001449465],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002436424,0.0009854677,0.002166661,0.0001643903,0.00019282,0.000006500739,0.003307533,0.00009285806,0.3152212,0.07407826,0.0316884,0.5718523],"study_design_scores_gemma":[0.0002354528,0.0009745178,0.0004142426,0.00008626664,0.00001119877,0.00006824946,0.006935497,0.0003440171,0.861856,0.1108804,0.01800067,0.0001934553],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9893664,0.0002143038,0.0000382234,0.002649719,0.0002836848,0.000346592,0.000005786652,0.0005155915,0.006579719],"genre_scores_gemma":[0.9982941,0.00009917909,0.0006653754,0.0001496272,0.00001424701,0.0003388663,2.147421e-7,0.000007655723,0.0004307684],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5716588,"threshold_uncertainty_score":0.3966124,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01053466421300405,"score_gpt":0.2365708682135916,"score_spread":0.2260362040005876,"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."}}