{"id":"W4240059842","doi":"10.1515/iupac.88.0257","title":"QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) Extraction","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Nuclear Physics and Applications","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; National Research Council Canada","funders":"","keywords":"Quechers; Computer science; Extraction (chemistry); Process engineering; Sample preparation; Scale (ratio); Data extraction; Sample (material); Biochemical engineering; Chromatography; Engineering; Chemistry; MEDLINE; Physics","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":[0.002312637,0.002446189,0.001969882,0.004685179,0.000890522,0.002534573,0.003340595,0.001813028,0.03409553],"category_scores_gemma":[0.009063277,0.0005260928,0.00187585,0.006861471,0.000558987,0.001835996,0.002678915,0.002030047,0.05647924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001649856,"about_ca_system_score_gemma":0.003293737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0133695,"about_ca_topic_score_gemma":0.03474591,"domain_scores_codex":[0.9981493,0.0003460405,0.000279013,0.0005679507,0.0004299193,0.0002278634],"domain_scores_gemma":[0.9971386,0.0009533431,0.000429069,0.0005662788,0.0007410785,0.0001715863],"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":[0.0002424955,0.00004268018,0.003994888,0.006284539,0.0001955121,0.00007571049,0.00004693427,0.0007073249,0.0008577278,0.001323497,0.9715749,0.01465383],"study_design_scores_gemma":[0.0001611807,0.00002749887,0.005815627,0.0009810239,0.0001033314,0.00009896229,0.00006456159,0.0003936953,0.0009933593,0.002046956,0.9892758,0.00003807862],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002278839,0.0004322877,0.0003152293,0.0000885378,0.00003921612,0.00002437103,0.9977489,0.0004157441,0.0007078968],"genre_scores_gemma":[0.000375637,0.0003252998,0.000768085,0.00007549887,0.000007487994,0.000102484,0.997754,0.00006546587,0.0005259539],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03409553,"threshold_uncertainty_score":0.1140609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009874555225320597,"score_gpt":0.4069275569591258,"score_spread":0.3970530017338052,"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."}}