{"id":"W4415474980","doi":"10.1681/asn.2025feyefqjk","title":"Assessing Open-Weight, Large Language Model for Symptom Extraction from Dialysis Notes: A Cost-Effective and Privacy-Preserving Approach","year":2025,"lang":"en","type":"article","venue":"Journal of the American Society of Nephrology","topic":"Topic Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier de l’Université de Montréal; McGill University Health Centre","funders":"","keywords":"Dialysis; Kidney disease; Hemodialysis; MEDLINE; Data extraction","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":[0.005381519,0.001502155,0.0007058205,0.001334053,0.0003977982,0.002263682,0.001386914,0.001134159,0.00201186],"category_scores_gemma":[0.02521681,0.0004172261,0.001270169,0.0006193497,0.0003623221,0.0027056,0.001780412,0.001332782,0.001592681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001097426,"about_ca_system_score_gemma":0.001726882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003348154,"about_ca_topic_score_gemma":0.004285741,"domain_scores_codex":[0.9964245,0.001639948,0.0003716503,0.000764761,0.0006842706,0.0001148307],"domain_scores_gemma":[0.9809352,0.01430695,0.0009471439,0.001652947,0.001852926,0.0003048363],"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":[0.004388544,0.001914923,0.04754728,0.002201911,0.0008871973,0.001003966,0.001441429,0.1086081,0.03977884,0.003031708,0.02139099,0.7678051],"study_design_scores_gemma":[0.0002735301,0.0009110099,0.009849652,0.000192031,0.0003781168,0.000550154,0.0006773783,0.9274737,0.03977117,0.006917817,0.01288314,0.0001224397],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3641501,0.001466332,0.58086,0.001632397,0.0002834147,0.001114259,0.00810805,0.03894853,0.003436891],"genre_scores_gemma":[0.599962,0.0003379696,0.3864246,0.0004545562,0.00008871742,0.000580248,0.01001002,0.0006031421,0.001538825],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005381519,"threshold_uncertainty_score":0.02846056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03270521271704304,"score_gpt":0.3448732067205751,"score_spread":0.3121679940035321,"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."}}