{"id":"W3047830475","doi":"10.1093/bioinformatics/btaa700","title":"FastBMD: an online tool for rapid benchmark dose–response analysis of transcriptomics data","year":2020,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Genome Canada","keywords":"Benchmark (surveying); Computer science; Transcriptome; Data mining; Biology","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":[0.0002497492,0.0001126959,0.0001944476,0.00008110623,0.00003936996,0.0000222345,0.0004814181,0.0001044414,0.00002940931],"category_scores_gemma":[0.0001664856,0.0001027964,0.0001115019,0.0002994557,0.00003751633,0.00001995673,0.0000795848,0.00004011737,0.00000113926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006143979,"about_ca_system_score_gemma":0.0001155771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000136395,"about_ca_topic_score_gemma":0.000006277813,"domain_scores_codex":[0.9990985,0.00003764912,0.0004136009,0.0001954324,0.000125731,0.0001290395],"domain_scores_gemma":[0.9988877,0.00001726582,0.0001773964,0.000717726,0.0001041414,0.00009576448],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00236994,0.0001763864,0.0005109544,0.0001421691,0.0005999299,1.519792e-7,0.0009819454,0.0008349476,0.9328162,0.00006242821,0.01558701,0.04591794],"study_design_scores_gemma":[0.001760062,0.00103689,0.009513251,0.00001158638,0.0008225624,0.000001038618,0.001556381,0.5235468,0.08987304,0.00000740395,0.3714634,0.0004075035],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7862084,0.0002314981,0.2079803,0.0008183341,0.0001226274,0.0004397876,0.004033636,0.0000220981,0.0001433485],"genre_scores_gemma":[0.93882,0.0002145983,0.0452482,0.001457068,0.0001247645,0.00001447657,0.01404966,0.00001581199,0.00005538941],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8429432,"threshold_uncertainty_score":0.4191914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07772542409987128,"score_gpt":0.3109088631813704,"score_spread":0.2331834390814991,"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."}}