{"id":"W4238510104","doi":"10.15406/aowmc.2016.04.00090","title":"Consumer Informatics and Health Information on Obesity","year":2016,"lang":"en","type":"article","venue":"Advances in Obesity Weight Management & Control","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Queen's University","keywords":"Health informatics; Obesity; Informatics; Health information; Business; Medicine; Health care; Political science; Nursing; Public health; Internal medicine","routes":{"ca_aff":false,"ca_fund":true,"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":[0.003235087,0.0002673077,0.0003312777,0.002792184,0.001593388,0.007265938,0.0004086229,0.003854029,0.05483333],"category_scores_gemma":[0.0179396,0.0001932257,0.0003790503,0.004698925,0.00263338,0.005144534,0.002840024,0.002394276,0.005692319],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002935842,"about_ca_system_score_gemma":0.003683092,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008691991,"about_ca_topic_score_gemma":0.00932952,"domain_scores_codex":[0.9961825,0.001762319,0.000202611,0.0002642568,0.001323539,0.0002648288],"domain_scores_gemma":[0.9831737,0.01147887,0.00149003,0.0005774443,0.001906488,0.001373524],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00007233001,0.0002140145,0.01214051,0.001019441,0.00004478605,0.0003285535,0.006690259,0.0001778737,0.0002439039,0.2391662,0.4043217,0.3355804],"study_design_scores_gemma":[0.00002058554,0.00006478155,0.01663827,0.002137965,0.00002787711,0.0005297414,0.003391452,0.0002413425,0.0001621074,0.05369971,0.9230511,0.00003502932],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01042412,0.04332244,0.002196498,0.2486235,0.002499399,0.0000922476,0.0009002523,0.0001980835,0.6917434],"genre_scores_gemma":[0.4544221,0.1697797,0.006295838,0.1089796,0.01123268,0.0003081411,0.001940612,0.0002328859,0.2468085],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05483333,"threshold_uncertainty_score":0.1834357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01414913214916837,"score_gpt":0.3538732177716556,"score_spread":0.3397240856224873,"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."}}