{"id":"W3004591506","doi":"10.1145/3380799.3380806","title":"Enabling Laboratory Medicine in Primary Care Through IT Systems Use","year":2020,"lang":"en","type":"article","venue":"ACM SIGMIS Database the DATABASE for Advances in Information Systems","topic":"Clinical Laboratory Practices and Quality Control","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke; HEC Montréal; Université du Québec à Trois-Rivières","funders":"","keywords":"Medical laboratory; Primary care; Medicine; Quality (philosophy); Test (biology); Electronic medical record; Health care; Medical record; Family medicine; Medical education; Medical emergency; Nursing","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":[0.01205168,0.0002780665,0.0003581456,0.002321783,0.001719822,0.006230805,0.0009339774,0.0009793148,0.004161507],"category_scores_gemma":[0.03682201,0.0003481305,0.0003623325,0.003477026,0.002307913,0.00336873,0.002857945,0.001078784,0.0005856546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004843127,"about_ca_system_score_gemma":0.008755352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03406302,"about_ca_topic_score_gemma":0.03760549,"domain_scores_codex":[0.9799461,0.01189934,0.001028434,0.001031731,0.004062152,0.002032195],"domain_scores_gemma":[0.9337353,0.04329394,0.009430891,0.003797636,0.00505449,0.004687787],"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":[0.0001762658,0.0006882926,0.448953,0.001575574,0.0001990054,0.0008805487,0.04657396,0.00149462,0.005168027,0.01074856,0.01234306,0.4711991],"study_design_scores_gemma":[0.0001277772,0.001703459,0.7799073,0.002042669,0.0002609786,0.001582569,0.03791649,0.004604829,0.003181568,0.01324379,0.1552919,0.0001365738],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8316851,0.01082071,0.02081286,0.04137015,0.0001549406,0.0004702066,0.000619107,0.0007891469,0.09327769],"genre_scores_gemma":[0.9865422,0.003086901,0.007639538,0.001556354,0.0001449209,0.00005626564,0.00009145923,0.00002194666,0.000860385],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03406302,"threshold_uncertainty_score":0.06772947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09073516943760598,"score_gpt":0.3753013259808948,"score_spread":0.2845661565432888,"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."}}