{"id":"W1574319978","doi":"10.1111/pme.12185","title":"An Artificial Neural Network Approach for Predicting Functional Outcome in Fibromyalgia Syndrome after Multidisciplinary Pain Program","year":2013,"lang":"en","type":"article","venue":"Pain Medicine","topic":"Fibromyalgia and Chronic Fatigue Syndrome Research","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Physical therapy; Fibromyalgia; Logistic regression; Anxiety; Hospital Anxiety and Depression Scale; Multidisciplinary approach; McGill Pain Questionnaire; Physical medicine and rehabilitation; Visual analogue scale; Internal medicine; Psychiatry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002257153,0.0006764044,0.0005441715,0.001264423,0.0002168985,0.0006714055,0.0004842332,0.000771047,0.001183036],"category_scores_gemma":[0.007627087,0.0001765615,0.0003827065,0.0005094145,0.0001471492,0.0004162123,0.0003792101,0.0006128308,0.0001793025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006821254,"about_ca_system_score_gemma":0.0004948966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004940542,"about_ca_topic_score_gemma":0.004905967,"domain_scores_codex":[0.9993426,0.0003964433,0.00005860002,0.00007407228,0.00007601892,0.0000522619],"domain_scores_gemma":[0.9978932,0.001504257,0.0002036072,0.00004732802,0.0002778677,0.00007373356],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002739705,0.00155299,0.4001223,0.0002068675,0.0008238438,0.0002725646,0.000123091,0.3890332,0.001465569,0.000464236,0.001952874,0.2012428],"study_design_scores_gemma":[0.00004628582,0.0004150704,0.02564315,0.00004521835,0.00007211931,0.00005435945,0.00004988265,0.9727223,0.0002942711,0.0004663485,0.0001771649,0.00001384454],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.948702,0.001811234,0.04510444,0.001036462,0.0001376769,0.0001901462,0.0006998889,0.0002300004,0.002088184],"genre_scores_gemma":[0.9917378,0.000241481,0.006988041,0.0000903723,0.00004133507,0.0001051571,0.0003402042,0.000004903615,0.0004506235],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004940542,"threshold_uncertainty_score":0.01193708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04158019929518908,"score_gpt":0.3237907342243034,"score_spread":0.2822105349291143,"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."}}