{"id":"W1993111295","doi":"10.1111/j.1745-4581.2005.00019.x","title":"DETECTION OF <i>LISTERIA</i> SP. IN MEAT AND MEAT PRODUCTS USING TECRA <i>LISTERIA</i> VISUAL IMMUNOASSAY AND BIOCONTROL VISUAL IMMUNOPRECIPITATE ASSAY FOR <i>LISTERIA</i> IMMUNOASSAYS AND A CULTURAL PROCEDURE","year":2005,"lang":"en","type":"article","venue":"Journal of Rapid Methods & Automation in Microbiology","topic":"Listeria monocytogenes in Food Safety","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Listeria; Listeria monocytogenes; Immunoassay; Food science; Visual inspection; Detection limit; Biology; Chromatography; Chemistry; Computer science; Bacteria; Artificial intelligence; Antibody","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003071659,0.0004411066,0.0009504036,0.0003670972,0.0001148565,0.00008675593,0.0002255989,0.0004963496,0.000003288796],"category_scores_gemma":[0.0006094037,0.000388512,0.0001314919,0.0002465412,0.0003648727,0.0001248397,0.0002482506,0.0002585386,1.918966e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001214908,"about_ca_system_score_gemma":0.0001547358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003232778,"about_ca_topic_score_gemma":0.00007261708,"domain_scores_codex":[0.9958794,0.001359179,0.001645322,0.0005758843,0.00009826115,0.0004419655],"domain_scores_gemma":[0.9977486,0.0001892113,0.001270545,0.0002560195,0.0004569488,0.00007867986],"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":[0.002179772,0.0001076483,0.0006807121,0.000270116,0.0001454665,0.00000178275,0.000537848,0.00004513532,0.9682727,0.000007210716,0.00001475803,0.02773682],"study_design_scores_gemma":[0.005019667,0.001390006,0.003160326,0.0001888083,0.0001226699,0.001816633,0.0003987548,0.001104561,0.9812999,0.00004498372,0.005045741,0.0004079566],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9767781,0.0107703,0.01051399,0.0002994058,0.0006477851,0.0009151265,0.00005109239,0.00001169768,0.00001243667],"genre_scores_gemma":[0.914616,0.001146059,0.08362769,0.0001837969,0.0002742218,0.00003728235,0.00005020525,0.00004888674,0.00001582686],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0731137,"threshold_uncertainty_score":0.9998567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03066432571614473,"score_gpt":0.3555109312306751,"score_spread":0.3248466055145304,"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."}}