{"id":"W4210772504","doi":"10.36255/exon-publications-digital-health-patient-generated-health-data","title":"Electronic Patient-Generated Health Data for Healthcare","year":2022,"lang":"en","type":"book-chapter","venue":"Digital Health","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Interoperability; Health care; Data science; Data sharing; Quality (philosophy); Reliability (semiconductor); Knowledge management; Field (mathematics); Business; Computer science; Risk analysis (engineering); Medicine; World Wide Web; Political science; Alternative medicine","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":[0.00103305,0.0006261357,0.0003112318,0.001925849,0.0008148608,0.003343182,0.0008990468,0.001489938,0.05145511],"category_scores_gemma":[0.002036472,0.0003051091,0.000367009,0.003574264,0.00102348,0.005029509,0.002241546,0.002136749,0.02529577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001295719,"about_ca_system_score_gemma":0.001632129,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001345558,"about_ca_topic_score_gemma":0.002577523,"domain_scores_codex":[0.9993827,0.0001512108,0.00003584051,0.0000697297,0.0003289392,0.00003145075],"domain_scores_gemma":[0.9991139,0.0005773389,0.00002683301,0.0001008413,0.00014351,0.00003769143],"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":[0.00001054395,0.00002389873,0.0001295309,0.0004754423,0.000005369054,0.00006828545,0.0005877392,0.0003683591,0.0005875951,0.3000235,0.4292335,0.2684864],"study_design_scores_gemma":[0.000001492278,0.000003983334,0.00009300018,0.000250113,0.000001475492,0.0001311591,0.0000751656,0.0001922482,0.0001333945,0.01651677,0.9825964,0.000004860088],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00102019,0.04840458,0.05610406,0.01246633,0.005279751,0.0002842416,0.002211135,0.0009632038,0.8732665],"genre_scores_gemma":[0.01667188,0.08168416,0.09000163,0.01199829,0.002981186,0.0003738512,0.004233396,0.0006966054,0.7913591],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.05145511,"threshold_uncertainty_score":0.1721345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1116762698217934,"score_gpt":0.4342026311089636,"score_spread":0.3225263612871702,"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."}}