{"id":"W4234073625","doi":"10.1515/iupac.78.0554","title":"Sample Cleanup","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Pesticide Residue Analysis and Safety","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Glossary; Sample (material); Pesticide; Chemical nomenclature; Relation (database); Computer science; Data science; Management science; Engineering; Ecology; Chemistry; Data mining; Biology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000433514,0.0003282219,0.0005666855,0.00002578989,0.0001914386,0.00007313181,0.0005474213,0.000313899,0.01867947],"category_scores_gemma":[0.0006415948,0.00009531942,0.0003145997,0.000256298,0.0000878784,0.00006158116,0.0001687196,0.0002615284,0.000008204289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001218781,"about_ca_system_score_gemma":0.00007114033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001566792,"about_ca_topic_score_gemma":0.01141691,"domain_scores_codex":[0.9977435,0.00009996159,0.0004103805,0.0004900289,0.0008205211,0.0004355568],"domain_scores_gemma":[0.9986258,0.0004889164,0.0002218869,0.0002029486,0.0002668526,0.0001936421],"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":[0.0000398318,0.00008599797,0.00004818861,0.000009846517,0.00005348396,0.00001773999,7.120063e-7,3.151633e-7,0.0001252867,0.000009772679,0.9479756,0.05163322],"study_design_scores_gemma":[0.0001253178,0.000180517,0.001620551,0.0000966635,0.0000979553,0.000003884516,0.00001122814,0.00000241435,0.00001328864,0.0004365332,0.997089,0.0003226588],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001077081,0.0004276125,0.00001827845,0.00154093,0.0001631383,0.0001171378,0.9965695,0.00004651727,0.00003982061],"genre_scores_gemma":[0.0001749574,0.001818973,0.000014274,0.0004269241,0.001477493,0.000005809737,0.9958783,0.000001427795,0.0002018636],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05131056,"threshold_uncertainty_score":0.9822176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01791056726002556,"score_gpt":0.3571301275107852,"score_spread":0.3392195602507596,"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."}}