{"id":"W4256485209","doi":"10.1515/iupac.88.1180","title":"Parthenogenesis","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Philosophy and History of Science","field":"Arts and Humanities","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":[0.001176961,0.001674735,0.001327864,0.005003984,0.001019937,0.002915997,0.002044515,0.001463463,0.1086584],"category_scores_gemma":[0.007215302,0.0007022367,0.001761167,0.006293348,0.0005308768,0.001656725,0.002363693,0.002208584,0.1043037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001542903,"about_ca_system_score_gemma":0.002925497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01522913,"about_ca_topic_score_gemma":0.02576661,"domain_scores_codex":[0.9985417,0.0002219108,0.0003132746,0.0004174584,0.0003326923,0.0001729727],"domain_scores_gemma":[0.9965361,0.001145782,0.0005224979,0.0008428034,0.0007500804,0.0002027767],"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":[0.0001845665,0.00002589602,0.002942923,0.003820634,0.00005831307,0.00008969704,0.0000806016,0.0003220002,0.0003837415,0.001832436,0.9714292,0.01882998],"study_design_scores_gemma":[0.00008118593,0.0000114942,0.005343241,0.0009884359,0.00002891019,0.0001322134,0.00007190343,0.0001018384,0.0002707476,0.00103432,0.9919155,0.0000200845],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002988495,0.000697009,0.0002434493,0.00009777219,0.00007905105,0.00003909517,0.9949306,0.0002988379,0.003315285],"genre_scores_gemma":[0.0008616663,0.0007496488,0.0007767716,0.0001679866,0.00001977802,0.000205687,0.9946567,0.0001068688,0.002454983],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1086584,"threshold_uncertainty_score":0.3634987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05659514587318571,"score_gpt":0.3957573916737442,"score_spread":0.3391622458005585,"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."}}