{"id":"W4416729251","doi":"10.3389/fpubh.2025.1675080","title":"Leveraging artificial intelligence community analytics and nanopore metagenomic surveillance to monitor early enteropathogen outbreaks","year":2025,"lang":"en","type":"article","venue":"Frontiers in Public Health","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Public Health Agency of Canada; Université Laval","funders":"Oxford Nanopore Technologies; Genome Canada","keywords":"Metagenomics; Analytics; Population; Disease surveillance; Public health; Shotgun sequencing; Public health surveillance; Resistome","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.001136052,0.001020234,0.000656032,0.002506249,0.000518957,0.001597524,0.0007677507,0.0006018293,0.0007737723],"category_scores_gemma":[0.002550124,0.0002412201,0.0006557485,0.001469219,0.0004731754,0.0007866211,0.001141043,0.0007123992,0.0003796545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002183662,"about_ca_system_score_gemma":0.002108462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08884771,"about_ca_topic_score_gemma":0.1700565,"domain_scores_codex":[0.9992027,0.0001481319,0.0000330998,0.0002504054,0.0002446232,0.0001209913],"domain_scores_gemma":[0.9981309,0.0004800213,0.0003270769,0.0001591567,0.000698773,0.0002040833],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008568478,0.0006349499,0.3923779,0.001211186,0.0009974247,0.0008914685,0.001165731,0.08682498,0.1850152,0.00376786,0.01356215,0.3126944],"study_design_scores_gemma":[0.00004786887,0.0004109238,0.149365,0.0001732077,0.0002664574,0.0002900366,0.001408482,0.7565528,0.05481488,0.01120428,0.02527533,0.0001908212],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7655724,0.004731331,0.1893337,0.004443953,0.0003352854,0.0005080214,0.01641316,0.005425476,0.01323671],"genre_scores_gemma":[0.8848644,0.0009777864,0.1026456,0.0008586526,0.0001189605,0.0001391681,0.007797648,0.00009516522,0.002502591],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08884771,"threshold_uncertainty_score":0.1766611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08397409808420737,"score_gpt":0.3368091781771669,"score_spread":0.2528350800929596,"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."}}