{"id":"W4253754204","doi":"10.1515/iupac.88.0711","title":"Eclampsia","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":[0.0008588699,0.0007176771,0.001118079,0.002961743,0.0004438123,0.001413267,0.001161552,0.0009780914,0.0552107],"category_scores_gemma":[0.01006737,0.0003828523,0.001318311,0.005018375,0.0002031992,0.001081257,0.001152816,0.001719174,0.02142666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009111145,"about_ca_system_score_gemma":0.001666896,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01377518,"about_ca_topic_score_gemma":0.02174198,"domain_scores_codex":[0.998679,0.0002072174,0.0004633734,0.0003371552,0.0001982586,0.0001150632],"domain_scores_gemma":[0.9963692,0.001208667,0.000968425,0.0005439049,0.0007398101,0.0001698923],"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":[0.0004372592,0.00003010785,0.009420429,0.007364577,0.0002086249,0.0001305866,0.00007179645,0.0002258966,0.0001729411,0.001482807,0.9570539,0.02340118],"study_design_scores_gemma":[0.0005801456,0.00004525236,0.04465551,0.006156663,0.0002415141,0.0005208572,0.0001936727,0.0003418664,0.0003162146,0.002637398,0.9442527,0.00005813855],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004813299,0.0007616657,0.0001552749,0.0001694096,0.00006292039,0.00007253096,0.9954708,0.00009904026,0.002727051],"genre_scores_gemma":[0.002370388,0.001490782,0.0007024357,0.0004267787,0.00005594271,0.0004852926,0.9923043,0.00005318431,0.002110891],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0552107,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0122634566592531,"score_gpt":0.4573200620888933,"score_spread":0.4450566054296402,"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."}}