{"id":"W2742786690","doi":"10.1080/24740527.2017.1325715","title":"Predicting treatment outcomes of pain patients attending tertiary multidisciplinary pain treatment centers: A pain trajectory approach","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Pain","topic":"Musculoskeletal pain and rehabilitation","field":"Medicine","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Université de Montréal; McGill University; Centre Hospitalier de l’Université de Montréal","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Pfizer Canada; Réseau québécois de recherche sur la douleur; Pfizer","keywords":"Medicine; Quality of life (healthcare); Physical therapy; Brief Pain Inventory; Depression (economics); Neuropathic pain; Chronic pain; Anesthesia","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.001381708,0.0003102275,0.0004200767,0.0018608,0.000800357,0.001306326,0.0006694797,0.0004959835,0.002943625],"category_scores_gemma":[0.005609015,0.0001577575,0.0007722519,0.001768945,0.0002172594,0.0007288564,0.001150234,0.001003169,0.0002982597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002105027,"about_ca_system_score_gemma":0.003256027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1023502,"about_ca_topic_score_gemma":0.1670967,"domain_scores_codex":[0.9993319,0.0002516837,0.0000749582,0.00007109379,0.0001154144,0.000154991],"domain_scores_gemma":[0.9976032,0.0006212464,0.000839292,0.00006786563,0.0004093177,0.0004590839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008662701,0.00006046525,0.9950002,0.00001332775,0.00004440839,0.00001183635,0.00005809881,0.0002559531,0.00003706255,0.00003883085,0.0002951939,0.004097954],"study_design_scores_gemma":[0.00003235412,0.0001512668,0.9887842,0.00005697365,0.00007536131,0.00007384676,0.0009230608,0.00923051,0.0000617929,0.0002467969,0.0003532358,0.0000105381],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939678,0.0003890179,0.001068144,0.0007333934,0.000015975,0.0001285725,0.002074182,0.00001829071,0.001604601],"genre_scores_gemma":[0.9965819,0.0001646293,0.001472572,0.00005210201,0.00001097777,0.0000567657,0.001437134,0.000004963903,0.0002190493],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1023502,"threshold_uncertainty_score":0.2035089,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02127674117350073,"score_gpt":0.2769144496975648,"score_spread":0.2556377085240641,"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."}}