{"id":"W2105352739","doi":"10.3899/jrheum.141440","title":"Optimal Strategies for Reporting Pain in Clinical Trials and Systematic Reviews: Recommendations from an OMERACT 12 Workshop","year":2015,"lang":"en","type":"article","venue":"The Journal of Rheumatology","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":174,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; McGill University; University of Toronto; McMaster University","funders":"National Cancer Institute; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Agency for Healthcare Research and Quality; Patient-Centered Outcomes Research Institute","keywords":"Medicine; Randomized controlled trial; Physical therapy; Visual analogue scale; Interpretability; Pooling; Clinical trial; Systematic review; MEDLINE; Internal medicine; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.8374185,0.000204574,0.01012527,0.0002960012,0.00009146064,0.0004665117,0.001106157,0.0001261673,0.0002955735],"category_scores_gemma":[0.7476867,0.00007592471,0.001271805,0.0003678407,0.00008029256,0.0005141835,0.00006548797,0.0003361002,0.00003717106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000233431,"about_ca_system_score_gemma":0.0002338232,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004588871,"about_ca_topic_score_gemma":0.0002953091,"domain_scores_codex":[0.601265,0.2936694,0.1017689,0.0006410619,0.002264338,0.0003913544],"domain_scores_gemma":[0.453037,0.347917,0.191845,0.003864769,0.002764311,0.000571964],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"qualitative","study_design_scores_codex":[0.0008836208,0.0006836804,0.358543,0.004728142,0.003363295,0.00003727246,0.02853286,0.002781064,0.00003117486,0.005676621,0.4265245,0.1682148],"study_design_scores_gemma":[0.008024476,0.002867872,0.00707006,0.02890838,0.007641524,0.008448006,0.4280056,0.1867312,0.000003645802,0.2220957,0.09882518,0.001378431],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8099225,0.01249747,0.1688959,0.005772601,0.0008994998,0.001913569,0.000005419709,0.000002503162,0.00009048743],"genre_scores_gemma":[0.9568349,0.002444672,0.03998922,0.0003542014,0.00007989004,0.00006337612,0.000005620358,0.00001596819,0.0002121661],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3994727,"threshold_uncertainty_score":0.6921432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8935088860749568,"score_gpt":0.6400927785423581,"score_spread":0.2534161075325987,"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."}}