{"id":"W2898749396","doi":"10.18653/v1/w18-5620","title":"Listwise temporal ordering of events in clinical notes","year":2018,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Institutes of Health; University of Toronto; Mayo Clinic","keywords":"Timeline; Computer science; Baseline (sea); Ranking (information retrieval); Downstream (manufacturing); Natural language processing; Information retrieval; Statistics; Engineering; Mathematics; Geology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004488372,0.0009102369,0.0007168951,0.006592295,0.0006780761,0.002101223,0.001077298,0.000878324,0.003910126],"category_scores_gemma":[0.03893181,0.000265498,0.0007233646,0.005158292,0.0003266758,0.003182105,0.001209645,0.001202567,0.001853283],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009264148,"about_ca_system_score_gemma":0.002523711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006341571,"about_ca_topic_score_gemma":0.01221892,"domain_scores_codex":[0.9941062,0.001571664,0.00103631,0.0008998373,0.002024591,0.0003614203],"domain_scores_gemma":[0.9684507,0.01843316,0.004226468,0.001901506,0.00589468,0.001093491],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002879021,0.0006067742,0.1670946,0.003338701,0.0005703787,0.0008393985,0.001034928,0.07833157,0.0308038,0.01809291,0.05607056,0.6403374],"study_design_scores_gemma":[0.0002364257,0.001698862,0.1183933,0.0005074583,0.0007529668,0.003285971,0.00127521,0.6951242,0.05211311,0.07140099,0.05487354,0.0003380111],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2644134,0.008069482,0.6493684,0.002104315,0.0007697035,0.0008112155,0.05557204,0.009907012,0.008984503],"genre_scores_gemma":[0.6438411,0.001760366,0.2858021,0.0002986742,0.0005492061,0.000483632,0.0632127,0.0006052449,0.003447016],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006592295,"threshold_uncertainty_score":0.02373707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08409123596687995,"score_gpt":0.3602126343501249,"score_spread":0.276121398383245,"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."}}