{"id":"W4250915980","doi":"10.1515/iupac.79.1104","title":"Cytochrome P420","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"History and advancements in chemistry","field":"Chemistry","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; Organic chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001361218,0.002167121,0.001862174,0.004068681,0.00112378,0.003129895,0.002237354,0.001700126,0.05916524],"category_scores_gemma":[0.00686449,0.0007497261,0.001523144,0.007819355,0.0003837898,0.001450634,0.001628174,0.001904501,0.0988268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001630682,"about_ca_system_score_gemma":0.003377922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01708336,"about_ca_topic_score_gemma":0.02666979,"domain_scores_codex":[0.9982399,0.0002710455,0.0002831051,0.0006036434,0.0004444697,0.0001578166],"domain_scores_gemma":[0.9978912,0.0004830339,0.0003293447,0.0005219906,0.0005629963,0.0002113732],"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":[0.0002498157,0.00003303634,0.002050245,0.002280525,0.00009117137,0.0000483136,0.00002070755,0.0002969861,0.0003967689,0.0005127996,0.9859369,0.008082711],"study_design_scores_gemma":[0.0003365081,0.00004071905,0.008596424,0.0004905455,0.0001134505,0.0001708506,0.00003880091,0.0003053087,0.0006188232,0.001406044,0.9878443,0.00003830552],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001923445,0.0003334052,0.0001012992,0.00008657905,0.00003055829,0.00001960999,0.9980349,0.0002409069,0.0009604777],"genre_scores_gemma":[0.0004307124,0.0002101983,0.0002469264,0.0000737181,0.000008972166,0.00007450188,0.9982509,0.00004139621,0.0006626019],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05916524,"threshold_uncertainty_score":0.1979274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01305548677701457,"score_gpt":0.389812092714733,"score_spread":0.3767566059377185,"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."}}