{"id":"W4232358423","doi":"10.1515/iupac.79.1557","title":"Log-Normal Transformation","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; Hazard; Toxicology; Chemistry; Philosophy; Biology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004302324,0.002615467,0.001951021,0.004951076,0.000710475,0.00411516,0.003183462,0.001661256,0.1184355],"category_scores_gemma":[0.03178832,0.0006218093,0.003442472,0.006363872,0.0006997662,0.002507442,0.002017061,0.003242892,0.1819701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001515588,"about_ca_system_score_gemma":0.002699607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009796578,"about_ca_topic_score_gemma":0.01235728,"domain_scores_codex":[0.9948755,0.0009235488,0.0008149085,0.001964178,0.001046775,0.0003751982],"domain_scores_gemma":[0.9910932,0.003310719,0.0005989421,0.002765598,0.002017117,0.0002144414],"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":[0.0003109247,0.00007949747,0.005231589,0.0009986333,0.0001961049,0.00005290146,0.00002683304,0.001319807,0.0001878534,0.001146535,0.9607104,0.02973892],"study_design_scores_gemma":[0.0004753809,0.000122802,0.01105292,0.0005481019,0.0001541305,0.000268101,0.0001691324,0.004282136,0.0008201309,0.007281075,0.9747386,0.00008744467],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0008555761,0.00034214,0.001917689,0.0002450272,0.0003079635,0.0001184505,0.9911228,0.002607487,0.002482821],"genre_scores_gemma":[0.004576667,0.0003145941,0.003911563,0.0002623366,0.0001122581,0.0006164451,0.9842044,0.0006682202,0.005333535],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1184355,"threshold_uncertainty_score":0.3962063,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01178491796872968,"score_gpt":0.3690084850790847,"score_spread":0.3572235671103551,"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."}}