{"id":"W4237681822","doi":"10.1515/iupac.81.0947","title":"Waldsterben","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Pesticide and Herbicide Environmental Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Ecotoxicology; Relation (database); Environmental risk assessment; Computer science; Ecology; Risk assessment; Biology; Data mining; Linguistics; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002745647,0.0004865972,0.0005252925,0.00004710953,0.0001980854,0.00003412258,0.0005721989,0.0002706358,0.1577739],"category_scores_gemma":[0.0001232752,0.000347667,0.0001582549,0.0001122927,0.0004726953,0.000132054,0.0009902613,0.0003340312,0.0002435348],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001089695,"about_ca_system_score_gemma":0.00003458918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008360218,"about_ca_topic_score_gemma":0.003065676,"domain_scores_codex":[0.9970801,0.00005545576,0.000405853,0.0006590852,0.001234726,0.0005647741],"domain_scores_gemma":[0.9988022,0.00006859699,0.0001960761,0.0007237766,0.0000104809,0.0001988399],"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":[0.00003689201,0.0001330849,0.0004335079,0.00001798175,0.00005072619,0.0000719763,0.000009859299,0.000004340473,0.00005450888,6.826997e-7,0.9943363,0.004850149],"study_design_scores_gemma":[0.0004234186,0.0001550434,0.002865374,0.0001022093,0.00009347164,0.0000122595,0.0000127644,9.693846e-7,0.00002577539,0.0002570363,0.9955679,0.0004837314],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004740626,0.00037276,0.00004145314,0.00060371,0.000360064,0.0002372944,0.9968069,0.00005005997,0.001053715],"genre_scores_gemma":[0.00007694043,0.001162036,0.0000544702,0.0008522107,0.0004193275,0.0000237782,0.9954887,0.00003703352,0.001885522],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1575304,"threshold_uncertainty_score":0.9998975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01103931184723282,"score_gpt":0.3517923829771552,"score_spread":0.3407530711299224,"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."}}