{"id":"W4237583310","doi":"10.1515/iupac.88.0609","title":"Cleavage, Meroblastic","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Effects and risks of endocrine disrupting chemicals","field":"Environmental Science","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; Data mining; Philosophy","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":[0.00102436,0.001519869,0.00127925,0.004725944,0.001101155,0.004014941,0.002141706,0.00139915,0.1990329],"category_scores_gemma":[0.009712686,0.0007124871,0.001451107,0.007036637,0.0004809879,0.002858322,0.002391984,0.001823004,0.1854947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001335144,"about_ca_system_score_gemma":0.002861002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01444947,"about_ca_topic_score_gemma":0.0243214,"domain_scores_codex":[0.9984688,0.0002260377,0.0003301169,0.0004996292,0.0002940456,0.0001813881],"domain_scores_gemma":[0.9966415,0.0009717523,0.0005629099,0.0008666814,0.000718176,0.0002389883],"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":[0.0001662666,0.00001250077,0.001923287,0.0020805,0.00003483383,0.00003664712,0.00004387567,0.000174922,0.000173359,0.001338081,0.9831629,0.01085296],"study_design_scores_gemma":[0.00007549301,0.000009263231,0.002635097,0.000542965,0.00002199057,0.00006913457,0.00005931575,0.00006774905,0.0001208475,0.00117808,0.9952068,0.00001333754],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001461446,0.0002786067,0.0001349997,0.0001041632,0.00005433129,0.00002247686,0.9957742,0.0003206153,0.003164486],"genre_scores_gemma":[0.0005743947,0.0003802427,0.0005054664,0.0001881618,0.00001975581,0.00009907038,0.9958021,0.0001471658,0.002283619],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1990329,"threshold_uncertainty_score":0.6658313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01172373213998938,"score_gpt":0.4529341423831776,"score_spread":0.4412104102431882,"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."}}