{"id":"W3159641106","doi":"10.1002/pds.5255","title":"Chronic pain patients' willingness to share personal identifiers on the web for the linkage of medico‐administrative claims and patient‐reported data: The chronic pain treatment cohort","year":2021,"lang":"en","type":"article","venue":"Pharmacoepidemiology and Drug Safety","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Université de Montréal; Centre Hospitalier de l’Université de Montréal; Centre hospitalier de l'Université Laval; Université du Québec en Abitibi-Témiscamingue","funders":"AstraZeneca; Genentech; Fonds de Recherche du Québec - Santé; Réseau québécois de recherche sur la douleur; Fondation de l’Université du Québec en Abitibi-Témiscamingue; Canadian Institutes of Health Research; Teva Pharmaceutical Industries","keywords":"Medicine; Linkage (software); Cohort; Chronic pain; Context (archaeology); Cohort study; Family medicine; Identifier; Physical therapy; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.02301891,0.0003605986,0.0007767975,0.00003895781,0.002133701,0.00001011198,0.0004166178,0.0002317861,0.0002826518],"category_scores_gemma":[0.006363454,0.0001778922,0.0001190971,0.0002324201,0.0003824559,0.0000842893,0.0002517858,0.0009821352,0.000008090729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007246406,"about_ca_system_score_gemma":0.002699509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004529377,"about_ca_topic_score_gemma":0.002722282,"domain_scores_codex":[0.981463,0.01493908,0.001528373,0.0008451389,0.0002714141,0.0009529867],"domain_scores_gemma":[0.9450868,0.05275916,0.0008263584,0.0007919783,0.0002839307,0.0002518113],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00139949,0.0004352637,0.5245184,0.002003836,0.00271562,0.00002468809,0.02937481,0.00009788339,0.0003055043,0.002616372,0.1828398,0.2536684],"study_design_scores_gemma":[0.006017371,0.00256402,0.07438619,0.00123617,0.0008456076,0.00001768436,0.02162962,0.0480727,0.0001991282,0.0005061994,0.8438888,0.0006365153],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7033676,0.03858301,0.004619357,0.2280786,0.004072929,0.01737282,0.003303654,0.0001174682,0.0004845134],"genre_scores_gemma":[0.9784206,0.005549411,0.00003187815,0.01209593,0.0009344928,0.001894742,0.0006136014,0.00003686156,0.0004224856],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.661049,"threshold_uncertainty_score":0.9991654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1355577786663425,"score_gpt":0.4567528707519106,"score_spread":0.3211950920855681,"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."}}