{"id":"W1908738074","doi":"10.1371/journal.pone.0136764","title":"Impact of Genomics Platform and Statistical Filtering on Transcriptional Benchmark Doses (BMD) and Multiple Approaches for Selection of Chemical Point of Departure (PoD)","year":2015,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Carcinogens and Genotoxicity Assessment","field":"Biochemistry, Genetics and Molecular Biology","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Canada; Carleton University","funders":"Health Canada","keywords":"Toxicogenomics; Benchmark (surveying); Computational biology; Genomics; Point of delivery; Biology; Computer science; Bioinformatics; Gene expression; Toxicology; Data mining; Gene; Genetics; Genome","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":[],"consensus_categories":[],"category_scores_codex":[0.0000809542,0.00007693233,0.0001703192,0.00002237324,0.00001093577,0.000003585222,0.00002788735,0.00007544376,0.000003481301],"category_scores_gemma":[0.00005198492,0.00006889964,0.00004217512,0.00001917822,0.00006131901,0.000003107911,0.00002111492,0.00003532992,2.046168e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001660573,"about_ca_system_score_gemma":0.00004710703,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001980864,"about_ca_topic_score_gemma":0.00001237354,"domain_scores_codex":[0.9995255,0.000007690778,0.0001546529,0.0001361185,0.00009040669,0.00008559258],"domain_scores_gemma":[0.9997235,0.00002784745,0.00006052502,0.0000638103,0.00006723494,0.00005706323],"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":[0.0007541769,0.0004601397,0.008685348,0.0001547798,0.0001838965,7.937717e-8,0.00008982589,0.00005735867,0.9889617,0.0001031282,0.00002223329,0.000527325],"study_design_scores_gemma":[0.0009028013,0.001326995,0.02264416,0.0000210135,0.00006210062,0.000003880177,0.00005228532,0.003050253,0.9717177,0.0001356614,0.000009108022,0.00007409151],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963349,0.0001305444,0.002793305,0.00001062543,0.000004953527,0.0002021234,0.0004920546,0.000001404537,0.0000301002],"genre_scores_gemma":[0.9850663,0.00002893049,0.01463982,0.000004608708,0.00003574019,0.00000868094,0.0002053612,0.000007236365,0.000003305744],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01724406,"threshold_uncertainty_score":0.2809646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08067598952260804,"score_gpt":0.2643352040240773,"score_spread":0.1836592145014693,"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."}}