{"id":"W2061187463","doi":"10.1111/jam.12505","title":"Investigation into <i>in vitro</i> and <i>in vivo</i> models using intestinal epithelial IPEC-J2 cells and <i>Caenorhabditis elegans</i> for selecting probiotic candidates to control porcine enterotoxigenic <i>Escherichia coli</i>","year":2014,"lang":"en","type":"article","venue":"Journal of Applied Microbiology","topic":"Escherichia coli research studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada; Ministry of Education, India; China Scholarship Council; Ministry of Earth Sciences","keywords":"Caenorhabditis elegans; Probiotic; Biology; Lactobacillus reuteri; Microbiology; Enterotoxigenic Escherichia coli; Enterotoxin; Antimicrobial; Lactobacillus; In vivo; Escherichia coli; In vitro; Gene; Bacteria; Genetics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009341518,0.0002702016,0.0005581937,0.0001830736,0.0001001922,0.00003704117,0.0001793859,0.0001755965,7.592675e-7],"category_scores_gemma":[0.0001347411,0.000250771,0.00005963936,0.0001854475,0.0001896027,0.00001693607,0.0001281379,0.0002893242,2.455709e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007247399,"about_ca_system_score_gemma":0.0001615003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007016972,"about_ca_topic_score_gemma":0.0003236326,"domain_scores_codex":[0.9982721,0.0001377736,0.000631959,0.0004124166,0.00006643773,0.0004792909],"domain_scores_gemma":[0.9990713,0.0001492476,0.0003204462,0.0001269149,0.0001773543,0.0001547315],"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":[0.001885402,0.00004553559,0.001026854,0.0001049955,0.00005657407,0.000002579256,0.0002440313,0.0008811291,0.9953898,0.00002059241,0.0001507971,0.0001917524],"study_design_scores_gemma":[0.003420784,0.0008000902,0.00007057044,0.0000803998,0.00003831665,0.00009653235,0.00007985703,0.001865633,0.991939,0.000392032,0.0009727588,0.0002439904],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9871601,0.0003476602,0.01120818,0.0002272416,0.00008864629,0.0008986525,0.00004220091,0.000004787812,0.00002252408],"genre_scores_gemma":[0.9775907,0.0001122377,0.02064843,0.001323332,0.000214175,0.00005326371,0.00001227681,0.00003338666,0.0000121832],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009569393,"threshold_uncertainty_score":0.9999945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007582873762615149,"score_gpt":0.2250666295794589,"score_spread":0.2174837558168437,"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."}}