{"id":"W4230900241","doi":"10.1515/iupac.88.1235","title":"Primitive Axis","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":[0.001081772,0.001611578,0.001189449,0.003191738,0.001087109,0.00394453,0.002321773,0.00151624,0.2315178],"category_scores_gemma":[0.0107918,0.0006149558,0.001582355,0.004624032,0.0004363677,0.002969465,0.002770452,0.001788874,0.2606559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001392736,"about_ca_system_score_gemma":0.002768505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01389385,"about_ca_topic_score_gemma":0.02397692,"domain_scores_codex":[0.9983917,0.0002798705,0.0002909907,0.0005483986,0.0002834935,0.0002055633],"domain_scores_gemma":[0.9963728,0.001079233,0.0003800527,0.0008311032,0.001068148,0.0002685802],"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":[0.0001652831,0.00001364606,0.001654079,0.001242939,0.00003362521,0.00003055637,0.00004889127,0.000129593,0.0001081677,0.001319299,0.9858188,0.009435115],"study_design_scores_gemma":[0.00007000403,0.00001256367,0.00249593,0.0004615957,0.00002160151,0.00006457622,0.00008981172,0.0001125236,0.0001369756,0.001441398,0.9950767,0.00001636356],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001527879,0.0001794295,0.0001794651,0.0001464314,0.00006919952,0.00003336134,0.9947878,0.0005055129,0.003945984],"genre_scores_gemma":[0.0007325617,0.000257103,0.000615473,0.0002295881,0.00002908476,0.0001777817,0.994747,0.000194619,0.003016814],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2315178,"threshold_uncertainty_score":0.7745042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01246230476051603,"score_gpt":0.4548421863990281,"score_spread":0.4423798816385121,"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."}}