{"id":"W4308991976","doi":"10.51224/srxiv.219","title":"webcam-based machine learning approach for three-dimensional range of motion evaluation","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Range (aeronautics); Motion (physics); Computer science; Artificial intelligence; Computer vision; Computer graphics (images); Engineering; Aerospace engineering","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001495474,0.000173418,0.0002348772,0.0002734459,0.0002025203,0.00006210432,0.0003821327,0.0001228091,0.0009401811],"category_scores_gemma":[0.00006627464,0.0001706577,0.0002101726,0.0001492642,0.0000187197,0.0001484598,0.0003539193,0.0004093512,0.000005841225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001117492,"about_ca_system_score_gemma":0.0002005271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007876277,"about_ca_topic_score_gemma":0.00001919827,"domain_scores_codex":[0.9980282,0.000227485,0.0003464084,0.0005398305,0.0007109917,0.0001470491],"domain_scores_gemma":[0.9987856,0.0001081341,0.0003645925,0.0003541839,0.000348425,0.0000390231],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005106975,0.0003781015,0.0006384066,0.0003178904,0.00006383057,4.697832e-7,0.00009680258,0.8662817,0.0002259708,0.002503307,0.0004827376,0.1289597],"study_design_scores_gemma":[0.0007962611,0.00009346811,0.0007623275,0.00002032423,0.00004676,0.000001174528,0.00000521568,0.9927934,0.0005298699,0.00449427,0.0002820434,0.0001748829],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0103862,0.000116909,0.984674,0.0001755859,0.0004450661,0.001218094,0.00003219331,0.0001616442,0.002790331],"genre_scores_gemma":[0.8691581,0.000002526762,0.1272714,0.0001437944,0.0001182902,0.0008165588,0.002072912,0.00002155754,0.0003948096],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.858772,"threshold_uncertainty_score":0.9999731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07146190949846808,"score_gpt":0.296875979793306,"score_spread":0.2254140702948379,"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."}}