{"id":"W4250629113","doi":"10.1073/iti0111108","title":"In This Issue","year":2011,"lang":"en","type":"letter","venue":"Proceedings of the National Academy of Sciences","topic":"Genomics, phytochemicals, and oxidative stress","field":"Biochemistry, Genetics and Molecular Biology","cited_by":104,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research; Wellcome Trust","keywords":"Computational biology; Biology; Data science; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000434551,0.0001317552,0.0001781894,0.0001085693,0.00004722619,0.00000892466,0.001101874,0.0004182981,0.00006225688],"category_scores_gemma":[0.0002553292,0.00009564363,0.00009873372,0.0001934631,0.0007989503,0.00001201835,0.000231643,0.0003940875,0.000003398413],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000141624,"about_ca_system_score_gemma":0.00003903604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000113264,"about_ca_topic_score_gemma":8.965274e-8,"domain_scores_codex":[0.9987304,0.00000643175,0.0002850928,0.0003334788,0.0004769704,0.0001676494],"domain_scores_gemma":[0.999352,0.00001909984,0.0004164038,0.00001204811,0.0001855075,0.00001490225],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000006664607,0.00001313567,0.0005780921,0.00007034258,0.00001232651,9.068381e-9,0.00004541712,8.630527e-7,0.4607438,0.0002497179,0.5382516,0.00002806982],"study_design_scores_gemma":[0.00008048363,0.00003058298,0.001157757,0.0000535258,0.000006303413,0.000002962884,0.0000144092,0.000002673306,0.7612724,0.01090495,0.2263704,0.0001035524],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.3774635,0.001654,8.225778e-7,0.4656671,0.0002087336,0.0007235961,0.0002206746,0.000008395888,0.1540532],"genre_scores_gemma":[0.7369707,0.0003495492,0.001720803,0.2441582,0.003875969,0.00004113766,0.000007721056,0.00002722241,0.01284866],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3595071,"threshold_uncertainty_score":0.3900234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03382053871042673,"score_gpt":0.2912802870911707,"score_spread":0.257459748380744,"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."}}