{"id":"W4240785515","doi":"10.1515/iupac.88.0460","title":"Androgen Receptor (AR)","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); Human reproduction; Computer science; Biology; Genetics; 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":[0.001182164,0.001119257,0.00153739,0.003520209,0.0005714706,0.002002883,0.001834701,0.001194148,0.07400957],"category_scores_gemma":[0.009004802,0.0005273992,0.001560217,0.007657069,0.0003279311,0.0015151,0.001347619,0.001827776,0.06080056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009498463,"about_ca_system_score_gemma":0.002223111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01658658,"about_ca_topic_score_gemma":0.0255253,"domain_scores_codex":[0.9985511,0.0002548056,0.0003569384,0.0004213452,0.000282561,0.0001331553],"domain_scores_gemma":[0.9958767,0.001528094,0.0007276922,0.0007828843,0.0009041335,0.0001804316],"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":[0.000161487,0.00001589168,0.003671907,0.003581139,0.000102932,0.00006152433,0.00003956841,0.0002295236,0.0002206442,0.000949193,0.9774283,0.01353776],"study_design_scores_gemma":[0.0001385213,0.00002150371,0.0122993,0.001511076,0.0001114074,0.0002078376,0.00006598118,0.0001000361,0.0001862131,0.001149926,0.9841779,0.00003039515],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002032377,0.0008018012,0.0001406753,0.0001166371,0.0000508434,0.00002069032,0.9965332,0.0001015707,0.002031385],"genre_scores_gemma":[0.001050043,0.001018039,0.0004450126,0.0002649255,0.00002822408,0.0001356029,0.9954967,0.00004275069,0.001518689],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07400957,"threshold_uncertainty_score":0.2475867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01222985556834871,"score_gpt":0.438790357058791,"score_spread":0.4265605014904423,"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."}}