{"id":"W3048960256","doi":"10.2196/19531","title":"Use of Tablets and Smartphones to Support Medical Decision Making in US Adults: Cross-Sectional Study","year":2020,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"mHealth; Health Information National Trends Survey; eHealth; Cross-sectional study; Medicine; Descriptive statistics; Odds; Telemedicine; Population; Family medicine; Psychological intervention; Psychology; Nursing; Health information; Health care; Environmental health","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001640182,0.0002220538,0.0003748351,0.0009642532,0.0006133239,0.000936592,0.000426143,0.0006044607,0.001698026],"category_scores_gemma":[0.005101957,0.0005568659,0.0007170995,0.001562832,0.0002639043,0.000952179,0.0008711307,0.0009616489,0.0003732358],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003357436,"about_ca_system_score_gemma":0.0006454641,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01100291,"about_ca_topic_score_gemma":0.01721846,"domain_scores_codex":[0.9987017,0.000315536,0.0002865223,0.0002070088,0.0003646961,0.000124492],"domain_scores_gemma":[0.9963379,0.0006439598,0.001755877,0.0002303203,0.0006597425,0.0003721525],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003104934,0.00009674668,0.9975191,0.00004092841,0.0000642622,0.00002113022,0.0003370387,0.000009069335,0.00004389303,0.00001207066,0.0002392983,0.001585481],"study_design_scores_gemma":[0.000007669114,0.000136402,0.997818,0.00004582992,0.00006109784,0.0001557885,0.00104517,0.0000936951,0.00003180364,0.00001303836,0.0005859897,0.000005556932],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964734,0.000659546,0.0001268668,0.0001137041,0.00001049371,0.00008929618,0.00165504,0.000004743948,0.0008669171],"genre_scores_gemma":[0.9973677,0.0005184012,0.0004260043,0.0002834267,0.00001674473,0.0001149422,0.0009997267,0.000003588847,0.0002695582],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01100291,"threshold_uncertainty_score":0.02187771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1391671243506875,"score_gpt":0.5096727901858158,"score_spread":0.3705056658351283,"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."}}