{"id":"W1544245149","doi":"10.2196/mhealth.4283","title":"Valuable Features in Mobile Health Apps for Patients and Consumers: Content Analysis of Apps and User Ratings","year":2015,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":247,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"mHealth; App store; Usability; Mobile apps; Internet privacy; Computer science; World Wide Web; Feature (linguistics); Human–computer interaction; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00496403,0.0002595034,0.0004109198,0.002107022,0.0003679196,0.001119324,0.0002675001,0.0002932951,0.0009795256],"category_scores_gemma":[0.02925153,0.0001553339,0.0007388537,0.001296196,0.0004541674,0.0008736548,0.001077695,0.0004442057,0.0002080163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005114473,"about_ca_system_score_gemma":0.0003684923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001025808,"about_ca_topic_score_gemma":0.001734313,"domain_scores_codex":[0.9964883,0.001267846,0.0004838459,0.0002818418,0.001317099,0.0001609715],"domain_scores_gemma":[0.9651619,0.02270073,0.00580566,0.0006484311,0.005051198,0.0006320823],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00077327,0.000220519,0.9150391,0.0005587377,0.0002270052,0.0001540311,0.0184588,0.0002309878,0.002663029,0.0001564884,0.0008807504,0.06063734],"study_design_scores_gemma":[0.0000181316,0.0003919436,0.9879172,0.00008284284,0.00008837762,0.000220036,0.007410767,0.001939088,0.0005572509,0.0001057511,0.001235589,0.00003302877],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978845,0.0001357231,0.0006601757,0.00005722547,0.000006406977,0.0001837534,0.0003286613,0.00001521469,0.0007283028],"genre_scores_gemma":[0.9970896,0.0001103596,0.001928582,0.00002873812,0.00001271808,0.0002321466,0.0003230351,0.000007859996,0.0002671181],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00496403,"threshold_uncertainty_score":0.02625257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.136110711666146,"score_gpt":0.4724791364333821,"score_spread":0.3363684247672362,"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."}}