{"id":"W7116846222","doi":"10.1097/cin.0000000000001406","title":"A Pilot Report on Extracting Symptom Onset Date and Time From Clinical Notes in Patients Presenting With Chest Pain","year":2025,"lang":"en","type":"article","venue":"CIN Computers Informatics Nursing","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Documentation; Context (archaeology); Triage; Usability; Personalization; Electronic health record; MEDLINE; Emergency department","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":[0.007243872,0.0008189603,0.0004944105,0.001524503,0.0007951524,0.00177619,0.0007931201,0.0009552126,0.002389356],"category_scores_gemma":[0.0398137,0.0003107713,0.0008622889,0.00110369,0.0004997451,0.001428401,0.001493505,0.0008369006,0.001524048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005518826,"about_ca_system_score_gemma":0.001849467,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00529477,"about_ca_topic_score_gemma":0.007599581,"domain_scores_codex":[0.9948735,0.002335067,0.001062344,0.001000275,0.0005499835,0.0001788401],"domain_scores_gemma":[0.9603807,0.03019557,0.001452446,0.002630055,0.004872259,0.0004689673],"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":[0.003628758,0.002168333,0.2275791,0.007844335,0.0004134476,0.007188492,0.01811828,0.005036152,0.06198623,0.0008974216,0.02153515,0.6436043],"study_design_scores_gemma":[0.001114106,0.007184918,0.5660141,0.004373705,0.002010979,0.01718472,0.02499104,0.05463906,0.1664104,0.003875257,0.1514742,0.0007273751],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8481391,0.003150227,0.1052188,0.002450171,0.000591999,0.005488278,0.02679916,0.003518593,0.004643613],"genre_scores_gemma":[0.6286426,0.002681497,0.3292525,0.0009907535,0.0003356421,0.002596946,0.0321674,0.000398385,0.002934207],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007243872,"threshold_uncertainty_score":0.03830969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02504376867143218,"score_gpt":0.3287631218124802,"score_spread":0.303719353141048,"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."}}