{"id":"W4392864611","doi":"10.1080/09593985.2024.2329960","title":"Personalizing rehabilitation for individuals with musculoskeletal impairments: Feasibility of implementation of the Measures Associated to Prognostic (MAPS) tool","year":2024,"lang":"en","type":"article","venue":"Physiotherapy Theory and Practice","topic":"Musculoskeletal pain and rehabilitation","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières; Centre intégré universitaire de santé et de services sociaux de la Capitale-Nationale; Université Laval; Centre for Interdisciplinary Research in Rehabilitation; Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"","keywords":"Medicine; Dashboard; Rehabilitation; Biopsychosocial model; Psychological intervention; Physical therapy; Nursing; Data science; Computer science","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":[0.04479813,0.0003071955,0.0004211437,0.0006601583,0.0008874062,0.001491411,0.0008371881,0.0008950602,0.002149231],"category_scores_gemma":[0.08959558,0.0003999294,0.0006684959,0.0005116789,0.0008358064,0.001333163,0.001994086,0.0008816662,0.0002616285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001223184,"about_ca_system_score_gemma":0.004914685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002113144,"about_ca_topic_score_gemma":0.003183593,"domain_scores_codex":[0.9749739,0.01794795,0.001944204,0.0006548092,0.00311995,0.001359129],"domain_scores_gemma":[0.9538853,0.03443884,0.003433171,0.001649108,0.005079054,0.001514553],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001228199,0.004935059,0.5363433,0.001764584,0.0001103362,0.001168966,0.1522606,0.00102452,0.003634304,0.0004420873,0.003033109,0.294055],"study_design_scores_gemma":[0.0006740563,0.01500266,0.8055314,0.001332095,0.0001637214,0.001352932,0.1550388,0.004527506,0.003180872,0.0007623042,0.01220071,0.0002329151],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910699,0.0001249837,0.002454755,0.001229547,0.00003007955,0.002652742,0.0001269682,0.00003551268,0.002275421],"genre_scores_gemma":[0.9912174,0.0001211987,0.006499758,0.0001647934,0.00001228399,0.001730545,0.0000476631,0.000006124497,0.0002002885],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04479813,"threshold_uncertainty_score":0.236918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01705198135081267,"score_gpt":0.3878590899447034,"score_spread":0.3708071085938907,"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."}}