{"id":"W4247378810","doi":"10.1515/iupac.88.1210","title":"Ploidy","year":2017,"lang":"fr","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009565846,0.001367736,0.00121097,0.004767583,0.001009677,0.002848834,0.00181411,0.001313088,0.1779945],"category_scores_gemma":[0.008909661,0.0006536352,0.001368122,0.007962612,0.0004938245,0.002710914,0.002350064,0.001902522,0.1876503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001415848,"about_ca_system_score_gemma":0.002117525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01525477,"about_ca_topic_score_gemma":0.019721,"domain_scores_codex":[0.9985157,0.0001763143,0.0003322714,0.0004788538,0.0003334885,0.0001634325],"domain_scores_gemma":[0.996464,0.001157724,0.0004441429,0.0008652413,0.000891045,0.0001778998],"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":[0.00009741927,0.00001351212,0.001429739,0.001677368,0.0000241286,0.00004153092,0.00006207251,0.0001783856,0.0002865743,0.00117796,0.9821904,0.01282088],"study_design_scores_gemma":[0.00004149546,0.000007935735,0.002591281,0.0003292056,0.00001012281,0.00005647469,0.00005974816,0.00005685995,0.0001293568,0.0008593052,0.9958453,0.00001301923],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000167074,0.0002394007,0.0001679779,0.0001055427,0.00005706312,0.00002429004,0.9955137,0.0003358053,0.0033891],"genre_scores_gemma":[0.0006236245,0.0003597832,0.0006411452,0.0001772197,0.00001773735,0.0001391892,0.995046,0.0001506592,0.002844654],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8220055,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01445512335858024,"score_gpt":0.4571254334727046,"score_spread":0.4426703101141244,"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."}}