{"id":"W4380344007","doi":"10.2196/preprints.49719","title":"Leveraging mHealth Technologies for Public Health (Preprint)","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preprint; Public health; Internet privacy; Business; Computer science; World Wide Web; Medicine; Nursing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.005181622,0.0004883459,0.0004044566,0.005410627,0.001389499,0.009825945,0.0009734891,0.001222419,0.04129606],"category_scores_gemma":[0.0130743,0.0003737987,0.0007536056,0.007385799,0.001329734,0.004669369,0.002214895,0.001314858,0.01580074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008179998,"about_ca_system_score_gemma":0.01389101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2831319,"about_ca_topic_score_gemma":0.3759837,"domain_scores_codex":[0.9961631,0.0005821852,0.0002733267,0.0002368931,0.002347952,0.0003965201],"domain_scores_gemma":[0.9895006,0.002910744,0.0006203386,0.0005680193,0.005725806,0.00067455],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003041911,0.00002713798,0.001649525,0.001648616,0.00003082292,0.0001074189,0.000731867,0.000123083,0.001395675,0.008831896,0.6895549,0.2958687],"study_design_scores_gemma":[0.000003947548,0.00002122593,0.005649322,0.001480608,0.00002656935,0.00005575757,0.0004587663,0.00007988617,0.000526101,0.00103386,0.9906439,0.00002000366],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.006831581,0.214677,0.01036297,0.1685224,0.05254382,0.001165194,0.01883942,0.00269339,0.5243644],"genre_scores_gemma":[0.0674509,0.4589945,0.02814429,0.04197195,0.03268426,0.0005677806,0.01456944,0.001337021,0.3542798],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2831319,"threshold_uncertainty_score":0.5629678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3113646610968536,"score_gpt":0.4977670397348641,"score_spread":0.1864023786380105,"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."}}