{"id":"W4406588972","doi":"10.1021/acs.analchem.4c03749","title":"Single-Cell Identification and Characterization of Viable but Nonculturable <i>Campylobacter jejuni</i> Using Raman Optical Tweezers and Machine Learning","year":2025,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Salmonella and Campylobacter epidemiology","field":"Agricultural and Biological Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Campylobacter jejuni; Chemistry; Viable but nonculturable; Optical tweezers; Identification (biology); Characterization (materials science); Raman spectroscopy; Biophysics; Nanotechnology; Bacteria; Optics; Physics","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":[0.0001839003,0.0003527092,0.0002496102,0.0003678444,0.0002360082,0.0003629838,0.0003374215,0.0005168348,0.000566086],"category_scores_gemma":[0.0003437941,0.0001936202,0.000197004,0.0001879284,0.0002942342,0.0003658574,0.0003264551,0.0003627975,0.0002386577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003933292,"about_ca_system_score_gemma":0.0002478619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002626742,"about_ca_topic_score_gemma":0.00448187,"domain_scores_codex":[0.9998155,0.000009944079,0.000008711546,0.00007493793,0.00006113049,0.00002982545],"domain_scores_gemma":[0.9998461,0.00003744876,0.00003514998,0.00001407129,0.00004954111,0.000017596],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001839657,0.000009444613,0.0008464818,0.00003519147,0.000002620344,0.00002762189,0.00002650895,0.0003363928,0.9950746,0.00004650531,0.00005235239,0.003523946],"study_design_scores_gemma":[0.000002901387,0.00009105308,0.01118304,0.00001037239,0.000008644974,0.00009248201,0.0001198404,0.02052374,0.966675,0.0001015197,0.001169955,0.00002140635],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.972321,0.0004341191,0.0247214,0.0001480188,0.00003711613,0.0000518761,0.0005284877,0.0003305952,0.001427382],"genre_scores_gemma":[0.9468314,0.0005880066,0.04935382,0.0001050659,0.00001484057,0.0001146833,0.0007843027,0.00007246498,0.002135465],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002626742,"threshold_uncertainty_score":0.005222857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02074843478614049,"score_gpt":0.2240980781763842,"score_spread":0.2033496433902438,"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."}}