{"id":"W4406268375","doi":"10.1038/s41467-024-55461-x","title":"Integrating artificial intelligence with mechanistic epidemiological modeling: a scoping review of opportunities and challenges","year":2025,"lang":"en","type":"review","venue":"Nature Communications","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina; McGill University; York University","funders":"National Institute of Allergy and Infectious Diseases; Natural Sciences and Engineering Research Council of Canada; Centers for Disease Control and Prevention; Notsew Orm Sands Foundation; National Institutes of Health; National Science Foundation","keywords":"Computer science; Data science; Management science; Transformative learning; Artificial intelligence; Risk analysis (engineering); Medicine; Engineering","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":[0.01046697,0.001276572,0.003102161,0.0101935,0.000579221,0.003248972,0.0020803,0.002406893,0.004850585],"category_scores_gemma":[0.04315286,0.0009667644,0.003546689,0.01105847,0.001351655,0.003821734,0.002026167,0.002461742,0.001026494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00243658,"about_ca_system_score_gemma":0.009764885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004913531,"about_ca_topic_score_gemma":0.008199942,"domain_scores_codex":[0.9966086,0.00136389,0.0009591838,0.0002993521,0.0006566484,0.0001123424],"domain_scores_gemma":[0.9444876,0.04986748,0.002126831,0.0006983617,0.002545491,0.0002743154],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"systematic_review","study_design_scores_codex":[0.00007578704,0.00005767834,0.0004851964,0.3202235,0.001198483,0.0001375705,0.0003528142,0.001445312,0.00021041,0.01378446,0.01571929,0.6463095],"study_design_scores_gemma":[0.00003425833,0.0001225273,0.001291317,0.584051,0.003204236,0.0005527897,0.0004495137,0.0007483154,0.0002742757,0.01795923,0.3912489,0.00006373043],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00007124885,0.9984103,0.0003966255,0.0006438952,0.00009239598,0.00001443433,0.00003255564,0.00000533432,0.0003330942],"genre_scores_gemma":[0.0008170119,0.9981332,0.0006160669,0.0002225404,0.00008679261,0.00003158324,0.00003822797,0.000003069477,0.00005153515],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01046697,"threshold_uncertainty_score":0.05535525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8000319687845833,"score_gpt":0.5615916172949389,"score_spread":0.2384403514896444,"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."}}