{"id":"W7125589449","doi":"10.1109/cascon66301.2025.00096","title":"Streamlining Epidemiological Model Generation Using Large Language Models","year":2025,"lang":"","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Representation (politics); Modeling language; Key (lock); Language model; Data modeling; Transmission (telecommunications)","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":[0.004899886,0.001250813,0.0007629345,0.001198387,0.0005948421,0.002266595,0.002206716,0.001036425,0.005591929],"category_scores_gemma":[0.02927072,0.001088085,0.001680883,0.0006780787,0.0007248058,0.002908912,0.002943091,0.002036578,0.001680615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009055082,"about_ca_system_score_gemma":0.002365704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003152002,"about_ca_topic_score_gemma":0.006263501,"domain_scores_codex":[0.9972159,0.001501385,0.0002212863,0.0003176358,0.000630532,0.0001133743],"domain_scores_gemma":[0.9765246,0.01868801,0.0007459843,0.002335341,0.001495659,0.0002103999],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004552167,0.000343952,0.006181358,0.001257644,0.0001901579,0.001165337,0.002198728,0.655834,0.03191188,0.07401691,0.009348778,0.2170961],"study_design_scores_gemma":[0.00004370597,0.00005470368,0.0001443196,0.00005280491,0.00003370373,0.00008847105,0.0001583204,0.9586899,0.009992635,0.02161027,0.009109749,0.00002138934],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01410222,0.00005100057,0.9766237,0.0003149803,0.00002602853,0.000216389,0.0004290181,0.007092654,0.001144011],"genre_scores_gemma":[0.1748437,0.0001748318,0.8195741,0.0001927029,0.00002107982,0.0005176262,0.001675465,0.001648427,0.001352046],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005591929,"threshold_uncertainty_score":0.02591342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1571493220646085,"score_gpt":0.3633828044896131,"score_spread":0.2062334824250046,"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."}}