{"id":"W4255292743","doi":"10.1515/iupac.78.0521","title":"Recovery","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); Chemical nomenclature; Computer science; Pesticide; Management science; Data science; Ecology; Chemistry; Engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001862407,0.001748635,0.001312381,0.005998552,0.001022663,0.002970602,0.003106748,0.002407849,0.140655],"category_scores_gemma":[0.01386019,0.0006029098,0.001679965,0.008727314,0.0005071558,0.003082146,0.002229321,0.002208383,0.1569101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002284259,"about_ca_system_score_gemma":0.003851112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02537033,"about_ca_topic_score_gemma":0.04432065,"domain_scores_codex":[0.9972863,0.0004465334,0.0005455266,0.0008456939,0.0005758618,0.0003000658],"domain_scores_gemma":[0.9949045,0.001354621,0.0005731074,0.001171905,0.001736969,0.0002590058],"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":[0.0000591459,0.00001449531,0.0008020189,0.0009341531,0.00002360566,0.00002636243,0.00002419146,0.0001611134,0.00008630671,0.0009481913,0.9927385,0.00418187],"study_design_scores_gemma":[0.0000966347,0.000009651751,0.001922752,0.000545187,0.00001869161,0.00005385841,0.0000788329,0.000175166,0.0001679262,0.001402452,0.995508,0.00002093115],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006945701,0.00008435518,0.00007588525,0.00009896764,0.0000242207,0.00001955298,0.9983143,0.0001903678,0.0011229],"genre_scores_gemma":[0.0002577135,0.00008263974,0.0003081043,0.000102214,0.000007062362,0.0001164798,0.9981975,0.00005194694,0.0008763382],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.140655,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01070497632264313,"score_gpt":0.3425057014062896,"score_spread":0.3318007250836465,"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."}}