{"id":"W2604629955","doi":"10.3233/978-1-61499-742-9-407","title":"Multi-EMR Structured Data Entry Form: User-Acceptance Testing of a Prototype","year":2017,"lang":"en","type":"article","venue":"Studies in health technology and informatics","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"SNC-Lavalin (Canada)","funders":"","keywords":"Variety (cybernetics); Computer science; Quality (philosophy); Point (geometry); Knowledge management; Artificial intelligence","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":[0.02474348,0.0007778365,0.0004910827,0.0007173212,0.0003774122,0.0007954365,0.001248729,0.001217956,0.005639592],"category_scores_gemma":[0.05466068,0.0004991816,0.0007526586,0.0002784028,0.0006142146,0.001320769,0.001126981,0.0006959133,0.001827401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000427921,"about_ca_system_score_gemma":0.0008505515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004357901,"about_ca_topic_score_gemma":0.0005365619,"domain_scores_codex":[0.9873054,0.008551775,0.001471334,0.0007695908,0.001493447,0.0004084675],"domain_scores_gemma":[0.9423124,0.04332849,0.0009006929,0.004440282,0.008011892,0.001006251],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.009687241,0.028762,0.07289177,0.002863067,0.0002434586,0.002179723,0.02896861,0.003930868,0.1100024,0.001673208,0.01196064,0.726837],"study_design_scores_gemma":[0.007410914,0.1658955,0.410759,0.001711309,0.0007804486,0.008425707,0.01520912,0.07949854,0.19472,0.002742742,0.1117315,0.001115135],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8976135,0.000101869,0.08019806,0.0005856384,0.0001305073,0.01583858,0.0008917159,0.001932954,0.002707145],"genre_scores_gemma":[0.7245454,0.0001594651,0.2531936,0.0005764178,0.00007313695,0.01479643,0.001299287,0.0006144332,0.004741836],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02474348,"threshold_uncertainty_score":0.1308576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2587234020781207,"score_gpt":0.5219441191481501,"score_spread":0.2632207170700294,"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."}}