{"id":"W4240360255","doi":"10.1515/iupac.81.0213","title":"Corrosive","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Chemistry and Chemical Engineering","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Ecotoxicology; Environmental risk assessment; Relation (database); Computer science; Ecology; Risk assessment; Biology; Data mining; Philosophy; Linguistics","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00009873062,0.0002762671,0.0002685154,0.00001408378,0.00004680683,0.00001802997,0.0003887119,0.000258272,0.03764927],"category_scores_gemma":[0.0001913406,0.0002141357,0.00009972809,0.00009457536,0.0001524135,0.00005410541,0.0003094265,0.0003217153,0.00002375269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005361357,"about_ca_system_score_gemma":0.00003896314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004218595,"about_ca_topic_score_gemma":0.00004703382,"domain_scores_codex":[0.9984635,0.000007592103,0.0002139134,0.0003763453,0.0006269791,0.0003117416],"domain_scores_gemma":[0.999202,0.00004231702,0.00008652302,0.0004828771,0.00001685745,0.0001694155],"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":[0.00001873101,0.00005023757,0.000005054252,0.00003555969,0.000009959497,0.00002884127,0.000002258343,0.00002022951,0.003103329,2.671273e-7,0.9959112,0.0008143752],"study_design_scores_gemma":[0.0002613904,0.0000225931,0.000006436901,0.0001087486,0.00002785077,0.00001208672,0.000002960896,0.000007679691,0.003397519,0.00004321923,0.9958026,0.0003068481],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002802783,0.00006217144,0.0001051808,0.0001222563,0.0002248422,0.0000737835,0.998613,0.00004679269,0.0004716866],"genre_scores_gemma":[0.00009306428,0.0001483354,0.00002614227,0.0001329216,0.00035457,0.000007775425,0.9982727,0.00001926062,0.0009452237],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03762551,"threshold_uncertainty_score":0.9632304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005273909765324163,"score_gpt":0.3215105069857432,"score_spread":0.316236597220419,"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."}}