{"id":"W2599844092","doi":"","title":"Context Sensitive Health Informatics: Many Places, Many Users, Many Contexts, Many Uses","year":2015,"lang":"en","type":"book","venue":"","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Health informatics; Context (archaeology); Informatics; Computer science; Data science; Internet privacy; Political science; Geography; Medicine; Public health; Nursing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.001119689,0.0009544693,0.0006438126,0.001161529,0.001821819,0.009079608,0.0009006303,0.002149686,0.01650769],"category_scores_gemma":[0.002162878,0.0006267686,0.0004154928,0.001956802,0.001955809,0.01233615,0.005038596,0.003987757,0.008471053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007902639,"about_ca_system_score_gemma":0.001440054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001134609,"about_ca_topic_score_gemma":0.004342524,"domain_scores_codex":[0.9988523,0.0003922523,0.00005290656,0.0001048882,0.0005212195,0.00007651828],"domain_scores_gemma":[0.9984396,0.001005621,0.00005544574,0.0001362975,0.0001728637,0.0001901373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002328788,0.00004868692,0.0006139318,0.0007356331,0.00002582303,0.0001813302,0.004181722,0.0001913829,0.001392511,0.06673761,0.4286588,0.4972093],"study_design_scores_gemma":[0.0000037835,0.00002067261,0.0006612025,0.000838572,0.0000140986,0.0008477233,0.002112478,0.0001702448,0.0002972262,0.03284562,0.962168,0.00002030214],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.006686346,0.2204903,0.05690425,0.07568419,0.01219341,0.0001851163,0.0007295875,0.002694365,0.6244324],"genre_scores_gemma":[0.07646175,0.1820959,0.06074156,0.05533829,0.01396769,0.000327529,0.001088803,0.00139049,0.6085879],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.01650769,"threshold_uncertainty_score":0.0552237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05688399244738207,"score_gpt":0.3957874235077455,"score_spread":0.3389034310603634,"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."}}