{"id":"W1593394624","doi":"10.1055/s-0038-1638839","title":"eHealth in North America","year":2013,"lang":"en","type":"article","venue":"Yearbook of Medical Informatics","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; Ontario Medical Association","funders":"","keywords":"eHealth; Health records; Government (linguistics); Electronic health record; Incentive; Business; Incentive program; Investment (military); Grey literature; Economic growth; Political science; MEDLINE; Health care; Economics","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":[0.0008835446,0.0001303914,0.0001833867,0.002222118,0.001041923,0.001573034,0.0003681096,0.0003332807,0.005253172],"category_scores_gemma":[0.002166395,0.0000870725,0.000233731,0.005268364,0.0004455366,0.0006866552,0.0007238604,0.0005212146,0.0003548529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008658496,"about_ca_system_score_gemma":0.02129398,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5972939,"about_ca_topic_score_gemma":0.6864657,"domain_scores_codex":[0.9991003,0.0001331195,0.00007200793,0.0001288643,0.0003732362,0.0001923488],"domain_scores_gemma":[0.9968902,0.0004557695,0.0005307018,0.00005040135,0.00165998,0.0004128831],"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":[0.0001483311,0.0001888009,0.3010316,0.00415264,0.0001538465,0.001450943,0.005900367,0.000257586,0.0009929778,0.01397964,0.09141123,0.5803321],"study_design_scores_gemma":[0.00001869123,0.00004275325,0.7727452,0.0026179,0.00008837456,0.0008210878,0.006750346,0.0001284183,0.0002577438,0.0007093343,0.2158006,0.00001955476],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.3450831,0.3277858,0.000961034,0.05304731,0.001316476,0.0002022049,0.01046446,0.0002304679,0.2609091],"genre_scores_gemma":[0.7970389,0.162977,0.002812232,0.01142503,0.0008182407,0.0002116936,0.004769898,0.00004086594,0.01990608],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.5972939,"threshold_uncertainty_score":0.8101554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04077532324216102,"score_gpt":0.4150663373555687,"score_spread":0.3742910141134077,"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."}}