{"id":"W4241201386","doi":"10.1515/iupac.88.0915","title":"Hypaxial","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; 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":[0.002092191,0.001320318,0.00117114,0.003860386,0.0009590504,0.004118094,0.001987681,0.001197924,0.2376517],"category_scores_gemma":[0.01965066,0.0007010518,0.001889518,0.007223447,0.0005610128,0.004042068,0.00313269,0.002108534,0.2508826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001209749,"about_ca_system_score_gemma":0.002699409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009982137,"about_ca_topic_score_gemma":0.01760747,"domain_scores_codex":[0.9971049,0.0006737151,0.0006155783,0.0007849581,0.0005458879,0.0002748519],"domain_scores_gemma":[0.9918748,0.002962842,0.0007943776,0.002218173,0.001747413,0.0004025126],"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":[0.0001063408,0.00001245897,0.0008599259,0.001111064,0.00003133681,0.0000215452,0.00004078248,0.000121541,0.00009222855,0.001390921,0.985652,0.01055978],"study_design_scores_gemma":[0.00006211599,0.00001261231,0.001738175,0.0005333301,0.00001525396,0.00005149543,0.00006179098,0.00014525,0.0001194535,0.001690958,0.9955527,0.00001680562],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002716504,0.0004169949,0.0005910751,0.0004399507,0.0002378973,0.0000729403,0.9882556,0.001312256,0.008401621],"genre_scores_gemma":[0.001209337,0.0005679058,0.00165419,0.0006799594,0.0001019018,0.0003891849,0.9889075,0.0007005949,0.005789331],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2376517,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01216026823912485,"score_gpt":0.4591047449810867,"score_spread":0.4469444767419618,"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."}}