{"id":"W2890645415","doi":"10.5210/ojphi.v10i2.9114","title":"An innovative mobile data collection technology for public health in a field setting","year":2018,"lang":"en","type":"article","venue":"Online Journal of Public Health Informatics","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Canada; University of Toronto; First Nations Health and Social Secretariat of Manitoba; Public Health Agency of Canada; Canadian Women's Health Network; Sunnybrook Health Science Centre","funders":"","keywords":"Data collection; Mobile technology; Computer science; Public health surveillance; Mobile device; Health informatics; Data science; Public health; World Wide Web; Knowledge management; Medicine; Nursing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005132378,0.00099502,0.0004464409,0.002262752,0.001269082,0.002303662,0.001888368,0.001444651,0.009998923],"category_scores_gemma":[0.01110514,0.000421961,0.0006265649,0.001324336,0.0008458094,0.002265837,0.003824745,0.00104973,0.002542341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00134118,"about_ca_system_score_gemma":0.004051807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.011237,"about_ca_topic_score_gemma":0.01307338,"domain_scores_codex":[0.9959039,0.00189375,0.000225695,0.0005073335,0.001071197,0.0003981499],"domain_scores_gemma":[0.9936812,0.003281663,0.0002373912,0.0005290544,0.001788273,0.0004824217],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001311145,0.0005652367,0.009921306,0.003451832,0.00009851572,0.001891104,0.01357842,0.001017037,0.04196729,0.009840488,0.06316493,0.8531927],"study_design_scores_gemma":[0.001189328,0.00395714,0.05354492,0.004055198,0.000515478,0.00516206,0.01673184,0.01886398,0.04170926,0.01904197,0.8344702,0.0007586568],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1717885,0.003219752,0.6574894,0.01514971,0.002402161,0.02463245,0.01180355,0.02166476,0.09184977],"genre_scores_gemma":[0.2855378,0.001638212,0.6698989,0.003836709,0.0005091046,0.01474434,0.002951403,0.00047101,0.02041242],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.011237,"threshold_uncertainty_score":0.03344971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1162394518348574,"score_gpt":0.4403923307946353,"score_spread":0.3241528789597779,"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."}}