{"id":"W2771182325","doi":"10.2196/mhealth.8764","title":"How Do Infant Feeding Apps in China Measure Up? A Content Quality Assessment","year":2017,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Usability; mHealth; App store; Mobile phone; Quality (philosophy); Android (operating system); Phone; Accountability; China; Information quality; Content analysis; Internet privacy; Mobile apps; Psychology; Medicine; Medical education; World Wide Web; Nursing; Computer science; Psychological intervention; Information system; Engineering; Geography","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":[0.03378684,0.0005706042,0.001233029,0.01497504,0.001644723,0.003046976,0.0009565673,0.0006242522,0.001051991],"category_scores_gemma":[0.1009013,0.0004061053,0.001944785,0.01311009,0.001853023,0.002919537,0.002727062,0.0006090315,0.0001449492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00594179,"about_ca_system_score_gemma":0.009408838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01689857,"about_ca_topic_score_gemma":0.01443821,"domain_scores_codex":[0.9787267,0.004896983,0.006003961,0.001510149,0.008161699,0.0007005502],"domain_scores_gemma":[0.8899566,0.04960439,0.01999657,0.003943524,0.03434977,0.002149123],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004237018,0.0002116466,0.7320036,0.006906809,0.0007129731,0.0003342821,0.03334238,0.0005190942,0.0014829,0.001156472,0.002431724,0.2204744],"study_design_scores_gemma":[0.0000771585,0.0004048182,0.9733112,0.001981074,0.0006670017,0.0001610858,0.01056668,0.002011489,0.001112882,0.000546647,0.009054101,0.0001059386],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9794901,0.004158931,0.003195198,0.001080626,0.00008185888,0.003656211,0.003415212,0.000104135,0.004817686],"genre_scores_gemma":[0.983497,0.001716361,0.007977227,0.0002339464,0.0000434672,0.003862189,0.00215903,0.00002857715,0.0004820831],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03378684,"threshold_uncertainty_score":0.1786841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2519549197496945,"score_gpt":0.526768691146591,"score_spread":0.2748137713968964,"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."}}