{"id":"W4252395905","doi":"10.1515/iupac.78.0135","title":"Aggregate Exposure","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; Computer science; Chemical nomenclature; Relation (database); Management science; Data science; Chemistry; Engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001096559,0.001467223,0.001439231,0.004424421,0.0005523983,0.002057409,0.001913654,0.001319882,0.1067413],"category_scores_gemma":[0.009347387,0.0004377298,0.001722497,0.00822098,0.000257971,0.001822746,0.001615958,0.001522758,0.0570402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001725795,"about_ca_system_score_gemma":0.002332844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02209633,"about_ca_topic_score_gemma":0.03429423,"domain_scores_codex":[0.9984595,0.0002122758,0.0003672744,0.0005067916,0.0003230421,0.000131175],"domain_scores_gemma":[0.9964091,0.001019251,0.0007354493,0.0005703777,0.001083516,0.0001822387],"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":[0.0001400825,0.00002180737,0.003288534,0.002541617,0.0001234169,0.00003113916,0.0000311826,0.0003038041,0.0001147549,0.0008561351,0.9849101,0.007637398],"study_design_scores_gemma":[0.0001972382,0.00002847269,0.0123931,0.001307753,0.0001118994,0.0001171374,0.00008835131,0.0001887609,0.0002000281,0.001847246,0.9834839,0.00003602245],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009334964,0.0001249457,0.00004065485,0.00005148919,0.00001595847,0.00001115154,0.9990118,0.00004761854,0.0006030547],"genre_scores_gemma":[0.0006916133,0.0002302091,0.0002158436,0.0001141718,0.00001555985,0.0001362046,0.9975345,0.00003056692,0.001031427],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1067413,"threshold_uncertainty_score":0.3570852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01047908419261616,"score_gpt":0.3348553179675891,"score_spread":0.3243762337749729,"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."}}