{"id":"W4414015504","doi":"10.11159/icbes25.118","title":"Monte Carlo Simulation and Optofluidic Techniques for Detecting Enterococcus faecalis and Enterococcus faecium","year":2025,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science","topic":"Microfluidic and Capillary Electrophoresis Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Science and Technology Council","keywords":"Enterococcus faecalis; Enterococcus faecium; Monte Carlo method; Enterococcus; Computer science; Microbiology; Biology; Mathematics; Statistics; Bacteria; Antibiotics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000847508,0.0003930019,0.0004735116,0.0005225435,0.0003440065,0.0004333998,0.0004169249,0.000696216,0.0005770766],"category_scores_gemma":[0.00228583,0.0003623587,0.0004220411,0.0004108291,0.0004075681,0.000408015,0.0003456484,0.0004757611,0.0001294699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007800307,"about_ca_system_score_gemma":0.00108072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005327559,"about_ca_topic_score_gemma":0.005095267,"domain_scores_codex":[0.9995968,0.0001426627,0.00001678166,0.00004487627,0.0001702515,0.00002866286],"domain_scores_gemma":[0.9988781,0.0007990699,0.0001011536,0.00006322281,0.0001235297,0.00003504476],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001410572,0.0000855814,0.002094292,0.0001144648,0.00007838455,0.00006520874,0.00005906691,0.9421438,0.02434426,0.01425697,0.0003242474,0.01629271],"study_design_scores_gemma":[0.000005868191,0.00001526345,0.000171289,0.000004067196,0.000004391335,0.00001595846,0.000002660945,0.9950011,0.003405864,0.0008902984,0.0004752881,0.000007919244],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1899477,0.001418997,0.7996228,0.000348252,0.00009661105,0.0001439765,0.0001855453,0.0009203675,0.007315799],"genre_scores_gemma":[0.709658,0.0005097957,0.2872919,0.0001251495,0.00003024632,0.0003101746,0.0001503112,0.0001053828,0.001818965],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005327559,"threshold_uncertainty_score":0.01059306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005743449196250291,"score_gpt":0.2188323704400704,"score_spread":0.2130889212438201,"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."}}