{"id":"W4280567810","doi":"10.1371/journal.pcbi.1009500","title":"Predicting knee adduction moment response to gait retraining with minimal clinical data","year":2022,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Osteoarthritis Treatment and Mechanisms","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Science Foundation","keywords":"Gait; Physical medicine and rehabilitation; Osteoarthritis; Retraining; Medicine; Physical therapy; Gait analysis; Test set; Computer science; Artificial intelligence; Machine learning; Pathology","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":[0.001900785,0.0009292233,0.0006671606,0.0006433973,0.0001582971,0.0005736459,0.000697046,0.0008907951,0.000784071],"category_scores_gemma":[0.006799876,0.0002499519,0.0008379287,0.0005150069,0.0003811234,0.0003676343,0.0004513997,0.0008124939,0.0003893592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004129705,"about_ca_system_score_gemma":0.0004731407,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005692678,"about_ca_topic_score_gemma":0.005794975,"domain_scores_codex":[0.9993942,0.0002191759,0.00005565659,0.0001886548,0.00008073758,0.0000616201],"domain_scores_gemma":[0.997381,0.001530083,0.0002886089,0.0003116044,0.0003627552,0.0001259469],"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":[0.001682132,0.001344196,0.09705523,0.0004067104,0.0003245158,0.000359646,0.0001161829,0.7649111,0.01002824,0.0005456459,0.006899385,0.116327],"study_design_scores_gemma":[0.00006326137,0.0006133672,0.03033599,0.0000406266,0.00004940978,0.0001392886,0.00004941619,0.9636932,0.003309306,0.0006983479,0.0009723125,0.00003548232],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9396718,0.0007591437,0.04829776,0.0004624597,0.000138041,0.0001758641,0.008580084,0.0007839238,0.00113094],"genre_scores_gemma":[0.9683562,0.0001787544,0.01534456,0.0001184885,0.000035359,0.0001310174,0.01534929,0.00002990623,0.0004565032],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005692678,"threshold_uncertainty_score":0.0113191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08998604220468466,"score_gpt":0.3483893077379286,"score_spread":0.258403265533244,"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."}}