{"id":"W4233584790","doi":"10.1515/iupac.88.0890","title":"Hershberger Bioassay","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; Data 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":[0.002439954,0.001403734,0.001370626,0.004102683,0.0008100692,0.002980859,0.002681163,0.001566083,0.07940773],"category_scores_gemma":[0.01227023,0.0006444582,0.001535448,0.005843112,0.000477765,0.001929219,0.002023869,0.002014141,0.09749996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001467521,"about_ca_system_score_gemma":0.003317729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01476351,"about_ca_topic_score_gemma":0.02495155,"domain_scores_codex":[0.9972771,0.0005395666,0.000523633,0.0006807031,0.0007935853,0.0001853684],"domain_scores_gemma":[0.9933134,0.002056362,0.0008607989,0.001650882,0.001868323,0.0002501971],"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":[0.0002235072,0.00004277243,0.003819951,0.002842683,0.00009085268,0.00003852374,0.00003795532,0.0004420993,0.0003358273,0.001555943,0.975132,0.01543787],"study_design_scores_gemma":[0.0001548897,0.00003102797,0.005923321,0.0007134501,0.00006065413,0.00006719046,0.00005771117,0.0002256017,0.000456865,0.001522467,0.9907557,0.00003110723],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002489848,0.00036657,0.0003031898,0.00009669847,0.00006205557,0.00005056094,0.9950445,0.0003181213,0.003509261],"genre_scores_gemma":[0.001064633,0.0004391404,0.0008554085,0.0001731949,0.00002276628,0.0002784088,0.9939659,0.0001051831,0.003095429],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07940773,"threshold_uncertainty_score":0.2656453,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01240954372526508,"score_gpt":0.4543294911455693,"score_spread":0.4419199474203042,"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."}}