{"id":"W4233290823","doi":"10.1515/iupac.88.0968","title":"Ketoacidosis","year":2017,"lang":"es","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":[0.001119185,0.0008709361,0.001410657,0.003103474,0.0005979167,0.001904059,0.001110333,0.001127516,0.05926714],"category_scores_gemma":[0.01011378,0.0003666888,0.001768846,0.004941796,0.0003014458,0.001301327,0.001344851,0.001540329,0.02320432],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001197942,"about_ca_system_score_gemma":0.002322376,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009658187,"about_ca_topic_score_gemma":0.01900063,"domain_scores_codex":[0.9983596,0.0002504706,0.0006790659,0.0003348593,0.0002488956,0.0001271296],"domain_scores_gemma":[0.9946548,0.001790138,0.001557551,0.0008134855,0.0009391998,0.0002448172],"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":[0.0009242283,0.00005601353,0.009290813,0.01358373,0.0003467719,0.000209424,0.00006451251,0.0003355338,0.0002284782,0.001435111,0.9325131,0.04101233],"study_design_scores_gemma":[0.0007114353,0.00007060447,0.0329349,0.009066588,0.0004031878,0.0008029538,0.0001690537,0.0003342173,0.0004333937,0.003144451,0.9518529,0.00007627621],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006138072,0.001395559,0.0001626662,0.0001916105,0.00007394081,0.0001113126,0.9939432,0.0001478418,0.003360175],"genre_scores_gemma":[0.002913779,0.002243354,0.0008323767,0.0004451649,0.00005218111,0.0005143427,0.9912478,0.00004948443,0.001701496],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05926714,"threshold_uncertainty_score":0.1982684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01374277503830581,"score_gpt":0.4579350794724755,"score_spread":0.4441923044341697,"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."}}