{"id":"W2320877891","doi":"10.1021/ac501660a","title":"Unique Ion Filter: A Data Reduction Tool for GC/MS Data Preprocessing Prior to Chemometric Analysis","year":2014,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Advanced Chemical Sensor Technologies","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Genome Alberta; Genome Canada","keywords":"Chemometrics; Feature selection; Chemistry; Data reduction; Pattern recognition (psychology); Dimensionality reduction; Data set; Linear discriminant analysis; Raw data; Data pre-processing; Reduction (mathematics); Filter (signal processing); Artificial intelligence; Data mining; Chromatography; Computer science; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004248634,0.002776756,0.001645356,0.005188709,0.0009362676,0.001946338,0.001885852,0.001059198,0.01515539],"category_scores_gemma":[0.008325961,0.001090753,0.001897097,0.003731213,0.0006289809,0.002018728,0.001758361,0.00242689,0.006572152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005996025,"about_ca_system_score_gemma":0.001675608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00156671,"about_ca_topic_score_gemma":0.002607454,"domain_scores_codex":[0.9982431,0.0002097439,0.0001982965,0.0004704641,0.0007493705,0.0001290842],"domain_scores_gemma":[0.9970283,0.001281875,0.0003538056,0.0003891287,0.000860488,0.00008638794],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000760696,0.000375164,0.00594668,0.001529907,0.000583578,0.0006341041,0.0005693415,0.005295287,0.1600642,0.004341969,0.07056135,0.7493377],"study_design_scores_gemma":[0.0002259864,0.0006089135,0.0213608,0.0002476494,0.0003254393,0.001749721,0.0003140807,0.2015103,0.4918661,0.009167096,0.2720746,0.0005492479],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006904917,0.0003146063,0.9265276,0.000135304,0.0001358936,0.0003086761,0.004784247,0.05973115,0.00115745],"genre_scores_gemma":[0.01209674,0.0002405078,0.9768275,0.0001336339,0.00005008835,0.0008398586,0.004529966,0.00378018,0.001501479],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01515539,"threshold_uncertainty_score":0.05069989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0370766042884756,"score_gpt":0.2970028178122823,"score_spread":0.2599262135238067,"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."}}