{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02842088,0.0009704859,0.0007170454,0.002065581,0.002047643,0.001930725,0.002556555,0.001973507,0.001901247],"category_scores_gemma":[0.08488867,0.00095024,0.001779935,0.001397851,0.002994628,0.001711648,0.002331507,0.001965993,0.001319304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001721113,"about_ca_system_score_gemma":0.00334812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01341291,"about_ca_topic_score_gemma":0.009004518,"domain_scores_codex":[0.9728402,0.01908302,0.001923067,0.00205051,0.00306812,0.001034992],"domain_scores_gemma":[0.873175,0.07913979,0.00725931,0.02284198,0.01577993,0.001804011],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00222919,0.006023629,0.9719319,0.0001276159,0.0003791031,0.0003158524,0.003672638,0.0006207932,0.001237937,0.0003793501,0.00142293,0.01165909],"study_design_scores_gemma":[0.00105172,0.003705444,0.9803901,0.0001324271,0.0004036974,0.0008419371,0.003640564,0.003680198,0.002062622,0.0003918009,0.00364001,0.00005953685],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956311,0.00006532814,0.001617786,0.000138239,0.00002326141,0.0005993139,0.001040232,0.00001433782,0.0008704523],"genre_scores_gemma":[0.9895,0.0000952824,0.002909324,0.0002712263,0.00003127264,0.0007798818,0.005714126,0.00003114098,0.0006678101],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02842088,"threshold_uncertainty_score":0.1503058,"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."}}