{"id":"W2091927856","doi":"10.1007/s10916-014-0157-3","title":"Learning from Colleagues about Healthcare IT Implementation and Optimization: Lessons from a Medical Informatics Listserv","year":2014,"lang":"en","type":"article","venue":"Journal of Medical Systems","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Wilfrid Laurier University; University of Ottawa","funders":"","keywords":"Health informatics; Health care; Informatics; Medical education; Computer science; Nursing; Medicine; Public health; Political science","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":[0.02476082,0.0006652013,0.0004331314,0.00096069,0.006033465,0.01259906,0.004081327,0.00714284,0.01130204],"category_scores_gemma":[0.06649671,0.000697898,0.0007332485,0.001031083,0.003345876,0.0167528,0.006639122,0.009573568,0.003857419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004129446,"about_ca_system_score_gemma":0.01192115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004529827,"about_ca_topic_score_gemma":0.01015538,"domain_scores_codex":[0.9836515,0.009735394,0.0005807465,0.00106736,0.00332596,0.001639058],"domain_scores_gemma":[0.9037158,0.06374727,0.003018448,0.004927565,0.009734505,0.01485651],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.000612335,0.008693202,0.03476907,0.0008551361,0.0001970482,0.001929218,0.08986155,0.006386571,0.003766392,0.02898994,0.1223807,0.7015588],"study_design_scores_gemma":[0.0008450313,0.004960589,0.02122952,0.002847234,0.0003570377,0.002789845,0.2998906,0.03139792,0.01056013,0.2166835,0.4076526,0.000785984],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.34803,0.00269487,0.0851511,0.4476581,0.001876846,0.0003350599,0.0001991223,0.002083771,0.1119712],"genre_scores_gemma":[0.8547023,0.002140922,0.08392996,0.0292333,0.001121373,0.0001854551,0.0002376057,0.00104968,0.02739934],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02476082,"threshold_uncertainty_score":0.1309493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06460005601551827,"score_gpt":0.4681745281673364,"score_spread":0.4035744721518181,"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."}}