{"id":"W4238354135","doi":"10.1515/iupac.81.0196","title":"Conceptual Model (in Ecological Risk Assessment)","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; Ecology; Relation (database); Risk assessment; Computer science; Biology; Data mining; 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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003170516,0.0003363378,0.0004112464,0.00002301234,0.0000517243,0.00002049956,0.0004639064,0.0004343535,0.01599606],"category_scores_gemma":[0.0002938403,0.0002585934,0.0001126917,0.0001105482,0.0003197164,0.00008793717,0.0003964369,0.0007971767,0.000006340897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001224139,"about_ca_system_score_gemma":0.0001070979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005746246,"about_ca_topic_score_gemma":0.000202186,"domain_scores_codex":[0.9979418,0.00003027687,0.0003655812,0.000540163,0.0006832383,0.0004389216],"domain_scores_gemma":[0.9991347,0.0001030319,0.0001326736,0.000437533,0.00001460031,0.0001774781],"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":[0.00002330038,0.0002090922,0.0001437736,0.00001407067,0.00001204122,0.00003732089,0.000005001163,0.005050849,0.0006446378,0.00000336495,0.9934996,0.000356998],"study_design_scores_gemma":[0.0007593547,0.00004616306,0.0001766736,0.00006721536,0.00003210915,0.000004413916,0.00001124186,0.00367518,0.0002196024,0.0002805397,0.9943139,0.0004136161],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01036168,0.00003133546,0.0004818906,0.00008638756,0.00008931602,0.0001161331,0.9882232,0.00004095555,0.0005691228],"genre_scores_gemma":[0.004910654,0.0003417281,0.0003307555,0.0001030596,0.0001809473,0.00002127776,0.9937822,0.00002041411,0.0003090275],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01598972,"threshold_uncertainty_score":0.9999866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009318197878914098,"score_gpt":0.3489075259755168,"score_spread":0.3395893280966027,"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."}}