{"id":"W4239854611","doi":"10.21203/rs.2.19115/v1","title":"Identifying cases of chronic pain using health administrative data: A validation study","year":2019,"lang":"en","type":"preprint","venue":"Research Square","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Chronic pain; Medicine; Data mining; Physical therapy; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","sts","research_integrity"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.03273426,0.0003761598,0.001053508,0.0007929372,0.00178087,0.00007707669,0.001635009,0.0006114087,0.000536778],"category_scores_gemma":[0.008772591,0.000372861,0.0001140048,0.0008505611,0.0002406627,0.0003222336,0.005167841,0.005555541,0.0002455827],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.003923777,"about_ca_system_score_gemma":0.02382639,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.08417103,"about_ca_topic_score_gemma":0.03388115,"domain_scores_codex":[0.9660599,0.02610807,0.002307282,0.001538691,0.002374482,0.00161164],"domain_scores_gemma":[0.9835564,0.008651493,0.001350696,0.003481606,0.002586925,0.0003728938],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0005363353,0.002293068,0.7717274,0.09237306,0.0004274452,0.0002405964,0.09739012,0.003314416,0.0002442684,0.0008119193,0.007947221,0.0226941],"study_design_scores_gemma":[0.0008200154,0.007897951,0.02057276,0.04849478,0.00009785206,0.000008186161,0.7798827,0.1346205,0.0005937395,0.00384208,0.001975895,0.001193545],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.96439,0.003836602,0.004513846,0.001363681,0.002037279,0.02142496,0.002080382,0.0001310814,0.0002221388],"genre_scores_gemma":[0.9959697,0.0004436354,0.0004368134,0.00004931866,0.00107802,0.000517928,0.001129393,0.00009545343,0.0002797775],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7511547,"threshold_uncertainty_score":0.9999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8512663934924372,"score_gpt":0.7169636063803724,"score_spread":0.1343027871120648,"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."}}