{"id":"W4280522237","doi":"10.3791/63535","title":"Biplanar Videoradiography Dataset for Model-based Pose Estimation Development and New User Training","year":2022,"lang":"en","type":"article","venue":"Journal of Visualized Experiments","topic":"Diabetic Foot Ulcer Assessment and Management","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Pose; Artificial intelligence; Translation (biology); Calcaneus; Software; Rotation (mathematics); Motion capture; Measure (data warehouse); Computer vision; Pattern recognition (psychology); Machine learning; Data mining; Motion (physics)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005185222,0.0001420477,0.0003291691,0.0004187342,0.0001503882,0.00004100909,0.0001076469,0.00002302334,0.0001028499],"category_scores_gemma":[0.00002181549,0.0001298475,0.00009116893,0.0001537316,0.00001982799,0.0001460375,0.00005581406,0.0001015159,5.980845e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001185844,"about_ca_system_score_gemma":0.00032195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000443994,"about_ca_topic_score_gemma":3.222743e-7,"domain_scores_codex":[0.998634,0.00003770915,0.0004846956,0.0001555835,0.0004926461,0.0001953936],"domain_scores_gemma":[0.9992896,0.00003739281,0.000299808,0.0001226321,0.00004645461,0.0002040743],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.01186144,0.00480515,0.00343585,0.0006676118,0.003829443,0.0002453536,0.01759224,0.019121,0.03864313,0.002768289,0.7517732,0.1452572],"study_design_scores_gemma":[0.04865617,0.005132362,0.001477369,0.000386669,0.001111245,0.000110669,0.004618802,0.1663129,0.04495954,0.0008873796,0.7255622,0.0007847374],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5449205,0.001397702,0.4488124,0.001973927,0.0008175679,0.001613334,0.0001790318,0.00004209847,0.0002434633],"genre_scores_gemma":[0.5852542,0.00001272082,0.4110613,0.002168959,0.000103311,0.0000992319,0.000954129,0.00004268781,0.000303513],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1471919,"threshold_uncertainty_score":0.5295027,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0850204497255692,"score_gpt":0.4393502074620809,"score_spread":0.3543297577365117,"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."}}