{"id":"W4254257305","doi":"10.1515/iupac.88.1513","title":"Zygote","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Relation (database); Computer science; Linguistics; Philosophy; Data mining","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":[0.001114788,0.001752541,0.001574863,0.004162371,0.001370643,0.004337198,0.002351226,0.001700594,0.2399873],"category_scores_gemma":[0.009472711,0.0008607805,0.001792838,0.007187929,0.0004312891,0.002605576,0.00282296,0.002206763,0.2347649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001612445,"about_ca_system_score_gemma":0.003169933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02371435,"about_ca_topic_score_gemma":0.03280608,"domain_scores_codex":[0.9980715,0.0002700092,0.0004001555,0.0005931584,0.0004255614,0.0002396389],"domain_scores_gemma":[0.9956863,0.001336293,0.0004986094,0.001104974,0.001110025,0.0002638422],"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":[0.000146684,0.00001215567,0.001087112,0.001442172,0.00003218241,0.00003630228,0.00004253409,0.0001453301,0.0001574109,0.001486629,0.9868775,0.008533872],"study_design_scores_gemma":[0.00007954682,0.000009726339,0.002597981,0.0004953769,0.0000203154,0.0000676096,0.00005244438,0.0000735772,0.0001437751,0.001322375,0.9951191,0.00001827908],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008822454,0.0001297972,0.000144863,0.00006702328,0.00004696294,0.00001853208,0.9967527,0.0003140079,0.002437897],"genre_scores_gemma":[0.000410706,0.0002101035,0.0004578995,0.0001409245,0.00001505416,0.00009165036,0.9966094,0.0001506508,0.00191364],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2399873,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02453049493886214,"score_gpt":0.4733344787357511,"score_spread":0.448803983796889,"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."}}