{"id":"W2800814333","doi":"10.2196/jmir.9326","title":"Reducing Negative Outcomes of Online Consumer Health Information: Qualitative Interpretive Study with Clinicians, Librarians, and Consumers","year":2018,"lang":"en","type":"article","venue":"Journal of Medical Internet Research","topic":"Health Literacy and Information Accessibility","field":"Health Professions","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; McGill University","funders":"Canadian Institutes of Health Research","keywords":"Thematic analysis; Qualitative research; Psychology; The Internet; Population; Personally identifiable information; Social psychology; Medicine; Computer science; World Wide Web; Sociology; Environmental health","routes":{"ca_aff":true,"ca_fund":true,"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":[0.03473351,0.000995094,0.001260194,0.002980476,0.01179774,0.004988588,0.002568696,0.002634959,0.002370999],"category_scores_gemma":[0.04763564,0.001013072,0.0005263948,0.003235749,0.01616646,0.004476324,0.007709971,0.003557931,0.000315851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008596634,"about_ca_system_score_gemma":0.008079257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007206976,"about_ca_topic_score_gemma":0.01205634,"domain_scores_codex":[0.9743609,0.02040474,0.0007746535,0.0009979384,0.001672498,0.001789305],"domain_scores_gemma":[0.9287407,0.06154296,0.002798109,0.00114962,0.003840156,0.001928504],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001578818,0.0000494149,0.0008977203,0.00009311177,0.000002218344,0.0003952741,0.9964451,0.00001243577,0.0002380449,0.0003134623,0.0001483299,0.001389024],"study_design_scores_gemma":[0.000008920794,0.00004279201,0.0006797212,0.0001408013,0.000004215975,0.0001480967,0.9965834,0.00006824574,0.0002510873,0.00025477,0.001809359,0.000008554534],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9881903,0.0006150877,0.003458374,0.002362838,0.00007126557,0.000921365,0.0001371961,0.00002305454,0.004220594],"genre_scores_gemma":[0.9899055,0.0008395903,0.004064365,0.001767656,0.00004797545,0.001425341,0.00008096858,0.00003890781,0.001829662],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03473351,"threshold_uncertainty_score":0.1836905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1731672284672497,"score_gpt":0.6076367213133319,"score_spread":0.4344694928460823,"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."}}