{"id":"W4256504391","doi":"10.1515/iupac.78.0137","title":"Aglycon","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Urologic and reproductive health conditions","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Glossary; Chemical nomenclature; Relation (database); Computer science; Environmental chemistry; Management science; Data science; Chemistry; Engineering; Data mining; 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":[0.001075937,0.001682989,0.001323203,0.005315815,0.0007480308,0.002859071,0.002743826,0.001881391,0.1173265],"category_scores_gemma":[0.009626817,0.0005888102,0.001389745,0.008738777,0.0003999809,0.002060294,0.002132476,0.001823962,0.1239591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001717699,"about_ca_system_score_gemma":0.003087965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02282431,"about_ca_topic_score_gemma":0.04596886,"domain_scores_codex":[0.9986942,0.0002506838,0.0002679698,0.0003804881,0.0002584133,0.0001481844],"domain_scores_gemma":[0.9967403,0.001152916,0.0004623874,0.0006283942,0.0007519704,0.0002640374],"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":[0.00006378839,0.00001451752,0.001020803,0.00114556,0.0000309898,0.0000276211,0.00002924501,0.0002324913,0.0000598167,0.0009178081,0.993187,0.003270357],"study_design_scores_gemma":[0.0001245503,0.00001083671,0.002015119,0.000526136,0.00002308055,0.00005353838,0.00005717875,0.0002101759,0.00009674064,0.001420034,0.9954451,0.00001757658],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006037727,0.00008801596,0.00005012129,0.00007194369,0.00001425978,0.00001096591,0.9987375,0.0001912922,0.0007755989],"genre_scores_gemma":[0.0002510634,0.0001097593,0.0001984451,0.00008881956,0.000007685141,0.0000852401,0.9985844,0.00006428918,0.000610337],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1173265,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02391156398755982,"score_gpt":0.4507423280831734,"score_spread":0.4268307640956136,"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."}}