{"id":"W4241999405","doi":"10.1515/iupac.78.0278","title":"Environmental Fate","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 Guelph","funders":"","keywords":"Glossary; Relation (database); Computer science; Pesticide; Management science; Data science; Environmental chemistry; Ecology; Chemistry; Engineering; Biology; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002996764,0.0006839582,0.000639169,0.00006190221,0.0002938347,0.00003864018,0.0006655258,0.000336904,0.2065919],"category_scores_gemma":[0.00007478903,0.0005183141,0.0002251066,0.00009601912,0.0008287915,0.0001771821,0.001249992,0.0004527667,0.0004493585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001745358,"about_ca_system_score_gemma":0.00003024187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000414525,"about_ca_topic_score_gemma":0.0009453353,"domain_scores_codex":[0.9961511,0.00007866537,0.000529076,0.0008959899,0.001594341,0.0007507715],"domain_scores_gemma":[0.9985259,0.00007324677,0.0002714629,0.0008471397,0.000003781919,0.0002785337],"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":[0.00005405329,0.0002701937,0.0009762085,0.00001470705,0.00007126051,0.0001094009,0.00001315812,0.000008645503,0.0003019481,4.646018e-7,0.9912145,0.006965535],"study_design_scores_gemma":[0.0006077156,0.0001992709,0.007374707,0.00007885315,0.0001271363,0.00002135697,0.00002577971,0.000001675974,0.00006654827,0.0001838032,0.9906264,0.0006867787],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002350387,0.000562414,0.00003851281,0.0003522261,0.0003846628,0.0003233203,0.9954011,0.00005640393,0.0005309072],"genre_scores_gemma":[0.000612519,0.002709482,0.00005228188,0.0007653316,0.0004231606,0.00003540979,0.9939116,0.00005737642,0.001432889],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2061426,"threshold_uncertainty_score":0.9997268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00971595668517978,"score_gpt":0.3287342596015855,"score_spread":0.3190183029164057,"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."}}