{"id":"W2130700275","doi":"10.1001/jama.285.13.1764-jms0404-2-1","title":"Electronic Medical Records: Saving Trees, Saving Lives","year":2001,"lang":"en","type":"article","venue":"JAMA","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Columbia College","funders":"","keywords":"Medical record; Medicine; Population; The Internet; Medical emergency; Medical practice; Medical care; Medical education; Computer science; Family medicine; World Wide Web","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":[0.0103122,0.001081514,0.0008988065,0.003682821,0.003918611,0.01544196,0.003040765,0.007101268,0.04841516],"category_scores_gemma":[0.0473023,0.0005564396,0.0008478126,0.005044871,0.008085076,0.04261377,0.008860038,0.008508431,0.03345733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002085051,"about_ca_system_score_gemma":0.004079259,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002524342,"about_ca_topic_score_gemma":0.003331492,"domain_scores_codex":[0.9899511,0.004791911,0.0006627004,0.0006837622,0.00346756,0.000442895],"domain_scores_gemma":[0.9631984,0.01912392,0.001762999,0.004909505,0.007468232,0.003537043],"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":[0.00005444551,0.00003483357,0.0006935609,0.0008006129,0.00004247271,0.0001683319,0.001568732,0.0001817062,0.0002548854,0.1138951,0.6625789,0.2197264],"study_design_scores_gemma":[0.000007722299,0.0000215542,0.000310413,0.0008839444,0.00001492623,0.0003539136,0.001093893,0.00007647366,0.000111217,0.05404904,0.9430522,0.00002472008],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.001619553,0.09078481,0.02244903,0.7749931,0.02704357,0.00008874531,0.001185786,0.001657437,0.08017803],"genre_scores_gemma":[0.06536943,0.2989154,0.1007325,0.3203825,0.0786708,0.0003635951,0.003348962,0.002082305,0.1301344],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.04841516,"threshold_uncertainty_score":0.1619648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04124588699648816,"score_gpt":0.3988548042460529,"score_spread":0.3576089172495647,"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."}}