{"id":"W4247506026","doi":"10.1515/iupac.79.2094","title":"Systems Biology","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Toxicology; Chemistry; Biology; Philosophy; Linguistics","routes":{"ca_aff":true,"ca_fund":false,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004674279,0.0004792415,0.0006480084,0.0001547299,0.00009019369,0.00003674822,0.0005860146,0.0008974039,0.000386329],"category_scores_gemma":[0.0001847779,0.0003675791,0.0003133493,0.0001367655,0.0001867121,0.000001609276,0.0003103264,0.0002009082,0.000003804646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001151585,"about_ca_system_score_gemma":0.000572068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006751354,"about_ca_topic_score_gemma":0.0003116414,"domain_scores_codex":[0.9976171,0.0002036668,0.0004863908,0.0008012234,0.0003861332,0.0005054441],"domain_scores_gemma":[0.9975969,0.00001718601,0.000325107,0.001444568,0.0004354539,0.0001808525],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006556755,0.00005926202,0.00003907632,0.0000586141,0.0004755534,0.000009184455,5.353498e-7,0.00003451659,0.001800303,0.000005894482,0.9967285,0.0007229613],"study_design_scores_gemma":[0.0004692582,0.0002662168,0.000008905382,0.00008213671,0.0002063235,0.00002251811,0.000006186148,0.000007809201,0.0002455748,0.00002066835,0.9982036,0.0004607746],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0007208253,0.009264237,0.0006163188,0.0001020416,0.0009989231,0.0002112597,0.9880375,0.00002004966,0.0000288701],"genre_scores_gemma":[0.0005866121,0.003078791,0.00001907319,0.0001198375,0.003294987,0.00002471407,0.9918238,0.00005153989,0.001000656],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.006185446,"threshold_uncertainty_score":0.9998776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008904584051264328,"score_gpt":0.3594597942768659,"score_spread":0.3505552102256016,"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."}}