{"id":"W4318934801","doi":"10.1097/j.pain.0000000000002861","title":"Sensitivity and specificity of algorithms for the identification of nonspecific low back pain in medico-administrative databases","year":2023,"lang":"en","type":"article","venue":"Pain","topic":"Musculoskeletal pain and rehabilitation","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Medicine; Prospective cohort study; Confidence interval; Diagnosis code; Algorithm; Cohort; Low back pain; Cohort study; Database; Internal medicine; Physical therapy; Population; Pathology; Alternative medicine; Computer science","routes":{"ca_aff":true,"ca_fund":false,"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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.06378324,0.001245943,0.001323831,0.006316432,0.0006367487,0.004033537,0.00187797,0.002426527,0.0007086782],"category_scores_gemma":[0.1810988,0.0008818498,0.00251282,0.002806129,0.000973593,0.00260906,0.002177444,0.001169328,0.0004266327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001460492,"about_ca_system_score_gemma":0.002065271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003174816,"about_ca_topic_score_gemma":0.003003094,"domain_scores_codex":[0.93874,0.03721876,0.008492455,0.005378823,0.008837066,0.00133287],"domain_scores_gemma":[0.7967163,0.1619924,0.0148338,0.006465715,0.01858734,0.001404447],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001528426,0.000252625,0.9703627,0.0002190854,0.001367331,0.00005900552,0.0001631567,0.006684397,0.0004851012,0.0002550097,0.0005154739,0.01810778],"study_design_scores_gemma":[0.0004869263,0.001494452,0.6923165,0.0006617766,0.002488921,0.001558771,0.0005968034,0.2906155,0.006091364,0.001727299,0.001813321,0.0001483627],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.975125,0.002628473,0.01694357,0.0003901518,0.0001227865,0.0005760359,0.001429247,0.0002220114,0.002562846],"genre_scores_gemma":[0.9803801,0.0003118789,0.01737373,0.0001164485,0.00003405631,0.0001529426,0.001508689,0.00002681887,0.00009543962],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9362168,"threshold_uncertainty_score":0.3373221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05929640143677844,"score_gpt":0.3443436335310778,"score_spread":0.2850472320942993,"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."}}