{"id":"W4236068286","doi":"10.1515/iupac.88.0880","title":"Hematopoiesis","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":[0.000998196,0.0008841854,0.000950203,0.003288771,0.0006204829,0.002368747,0.001470554,0.001110938,0.08098764],"category_scores_gemma":[0.007857755,0.0004808639,0.001128615,0.004903328,0.0002752132,0.001487424,0.00151102,0.001482227,0.04627191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001034169,"about_ca_system_score_gemma":0.002134776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009863775,"about_ca_topic_score_gemma":0.01953027,"domain_scores_codex":[0.9990662,0.000150537,0.0002204281,0.0002525501,0.0001956233,0.0001146309],"domain_scores_gemma":[0.9973879,0.0008991908,0.0003552121,0.0005964732,0.0006074643,0.0001536334],"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":[0.000228374,0.00002059327,0.004991626,0.003453767,0.00008800977,0.00005572968,0.00005128954,0.0003048742,0.000323178,0.001475924,0.9586345,0.03037202],"study_design_scores_gemma":[0.0001430497,0.00001781121,0.008263271,0.001246234,0.00006809766,0.0001794198,0.0000559558,0.0001703162,0.0003373708,0.001906836,0.9875908,0.00002096118],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003622014,0.0008686867,0.0002326091,0.0002040497,0.00007710194,0.00003908875,0.9945027,0.0003120601,0.003401557],"genre_scores_gemma":[0.001673466,0.001107997,0.001070514,0.0003553231,0.0000393085,0.000189137,0.9933608,0.00008412158,0.002119289],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08098764,"threshold_uncertainty_score":0.2709306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01180932647536041,"score_gpt":0.4555756947207681,"score_spread":0.4437663682454077,"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."}}