{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003904054,0.0009176185,0.0004393612,0.0002302157,0.0002121229,0.0003935246,0.0003302456,0.0005554132,0.0009521473],"category_scores_gemma":[0.0001601854,0.0001565334,0.0005390577,0.0001432463,0.0003330164,0.0003923826,0.0002788446,0.0009776759,0.0003742048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003501285,"about_ca_system_score_gemma":0.0002712549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008151248,"about_ca_topic_score_gemma":0.00166084,"domain_scores_codex":[0.9997142,0.00005069001,0.0000319643,0.00006671099,0.00007724616,0.00005919507],"domain_scores_gemma":[0.9996986,0.0000431614,0.0001180447,0.00003909294,0.00005431566,0.00004673256],"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":[0.0001036671,0.00006381666,0.0003007039,0.00006835125,0.000004261293,0.00002595959,0.000009197135,0.00003645219,0.9988583,0.00002056873,0.00004329548,0.0004653955],"study_design_scores_gemma":[0.00002335513,0.002048577,0.006386445,0.0000209809,0.00004224267,0.0001704942,0.0000650048,0.0006395478,0.9894135,0.00002106261,0.001159964,0.000008803394],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.98551,0.002071472,0.008070085,0.000345216,0.0001210631,0.0002192189,0.001082706,0.000210205,0.00237012],"genre_scores_gemma":[0.9795631,0.001990915,0.0116495,0.0003387825,0.00003533499,0.0002701383,0.001886705,0.00005617077,0.004209364],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009521473,"threshold_uncertainty_score":0.003185272,"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."}}