{"id":"W3005992664","doi":"10.2196/14375","title":"Understanding and Preventing Health Concerns About Emerging Mobile Health Technologies","year":2020,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Science Foundation","keywords":"mHealth; Worry; Public health; Internet privacy; Digital health; Medicine; Population; Health care; Psychology; Computer science; Psychological intervention; Political science; Nursing; Environmental health; Psychiatry; Anxiety","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":[0.005590153,0.0005936935,0.000588027,0.001668248,0.001476913,0.005772713,0.001067504,0.005354076,0.003836538],"category_scores_gemma":[0.02306581,0.0004195431,0.0009241169,0.001076816,0.00374409,0.006406358,0.003527533,0.004708694,0.000659488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001883129,"about_ca_system_score_gemma":0.004878248,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003391539,"about_ca_topic_score_gemma":0.003585614,"domain_scores_codex":[0.9955477,0.002634303,0.0002773938,0.0003226297,0.0008550051,0.0003631033],"domain_scores_gemma":[0.9830396,0.01293432,0.002108754,0.000238763,0.001303003,0.000375554],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00009005685,0.0002931677,0.01600787,0.02319482,0.0001606252,0.001651849,0.04042156,0.0008315576,0.001748465,0.113361,0.03473788,0.7675012],"study_design_scores_gemma":[0.00004765882,0.0003999227,0.02057025,0.05267351,0.0004247963,0.00363461,0.04537035,0.001018009,0.001807897,0.08093007,0.7929958,0.0001271857],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.03936375,0.5571077,0.01537377,0.302268,0.0033479,0.0003581335,0.0002193529,0.0001228177,0.08183842],"genre_scores_gemma":[0.2609929,0.6563033,0.007932886,0.06376628,0.004068488,0.0004521867,0.0001680423,0.00002695326,0.006288955],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005772713,"threshold_uncertainty_score":0.0295639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2508126542023806,"score_gpt":0.4979073161853891,"score_spread":0.2470946619830085,"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."}}