{"id":"W2949132496","doi":"10.2196/13772","title":"Factors Determining Patients’ Choice Between Mobile Health and Telemedicine: Predictive Analytics Assessment","year":2019,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Telemedicine and Telehealth Implementation","field":"Medicine","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Telemedicine; mHealth; Telecare; Medicine; Health care; Medical emergency; Family medicine; Nursing; Psychological intervention","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007304174,0.0003692567,0.001029726,0.0003773434,0.0003475119,0.00002366101,0.0000768643,0.0001441104,0.00007482343],"category_scores_gemma":[0.00008661033,0.0002927064,0.00005149737,0.0003794385,0.0001022257,0.0001890067,0.00006972592,0.000627147,0.000005148412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004156257,"about_ca_system_score_gemma":0.001346509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004543932,"about_ca_topic_score_gemma":0.00004470579,"domain_scores_codex":[0.9964048,0.0001641132,0.001125239,0.000667579,0.0006565368,0.0009817684],"domain_scores_gemma":[0.9964405,0.0004443949,0.0006333496,0.0003468777,0.0001630897,0.001971834],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006194491,0.000118914,0.9157153,0.002707175,0.00003495779,0.000001122711,0.00186319,4.700668e-7,0.000001694997,0.00003492994,0.001294337,0.07816599],"study_design_scores_gemma":[0.004953723,0.01420405,0.9640482,0.0002440396,0.000127328,0.000006919854,0.003489147,0.0003112093,0.000003479759,0.0000214403,0.01240445,0.00018601],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924148,0.0006666057,0.0001699824,0.001905008,0.0002692705,0.004068704,0.0001033356,0.0001165699,0.0002857528],"genre_scores_gemma":[0.9909812,0.0009474152,0.0006105316,0.005940659,0.0004448434,0.0001629175,0.0007683556,0.00004864557,0.00009548673],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07797997,"threshold_uncertainty_score":0.9999525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07059595462664307,"score_gpt":0.4343094481650075,"score_spread":0.3637134935383644,"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."}}