{"id":"W4245954674","doi":"10.1515/iupac.88.1382","title":"Superfetation","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; 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":[0.002408555,0.001569615,0.001547678,0.005070796,0.001039671,0.003649964,0.002779685,0.001878423,0.1411087],"category_scores_gemma":[0.01673302,0.000692005,0.002214066,0.007841568,0.000540544,0.003112402,0.003471294,0.002353477,0.1659902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001535352,"about_ca_system_score_gemma":0.00384962,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01116581,"about_ca_topic_score_gemma":0.02578985,"domain_scores_codex":[0.9973058,0.0006083156,0.0005800975,0.000725192,0.000497817,0.0002828574],"domain_scores_gemma":[0.993296,0.002234887,0.0007416437,0.001663272,0.001643006,0.0004212621],"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":[0.0001001846,0.00001647584,0.001063611,0.002174036,0.0000483981,0.00002800423,0.00004365683,0.0001500982,0.0001484228,0.001108546,0.9890865,0.006031996],"study_design_scores_gemma":[0.0001192866,0.00001670862,0.002011792,0.0007567788,0.00002826115,0.00004871089,0.000058807,0.000143344,0.000184609,0.001179384,0.9954305,0.00002182778],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008689261,0.000161746,0.000145837,0.0001143516,0.00005501241,0.00003230388,0.9975895,0.0004144866,0.001399955],"genre_scores_gemma":[0.0002622276,0.0001678434,0.0004886712,0.0001540124,0.00001474339,0.0001885076,0.9975217,0.0001376349,0.001064782],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1411087,"threshold_uncertainty_score":0.4720557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.012188450196897,"score_gpt":0.4589388310081923,"score_spread":0.4467503808112953,"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."}}