{"id":"W2760720395","doi":"","title":"Solid Phase Microextraction as a Sample Preparation Tool for Targeted and Untargeted Analysis of Biological Matrices","year":2017,"lang":"en","type":"dissertation","venue":"UWSpace (University of Waterloo)","topic":"Biosimilars and Bioanalytical Methods","field":"Immunology and Microbiology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Concordia University","keywords":"Solid-phase microextraction; Sample preparation; Chromatography; Sample (material); Chemistry; Gas chromatography–mass spectrometry; Mass spectrometry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004628025,0.0006990843,0.000484865,0.0005184003,0.0003745013,0.0008125691,0.0004396306,0.0008393548,0.002159886],"category_scores_gemma":[0.0002820322,0.0003751298,0.0004946995,0.0004920332,0.0004174813,0.000537778,0.000550069,0.001106196,0.002308107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004650541,"about_ca_system_score_gemma":0.0005369029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002688986,"about_ca_topic_score_gemma":0.0006515734,"domain_scores_codex":[0.9991462,0.0001066152,0.00003451225,0.000235695,0.0004272429,0.00004969645],"domain_scores_gemma":[0.9998517,0.00005044369,0.00001999058,0.00002020914,0.00004573535,0.0000118601],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002857349,0.00003488047,0.00009521527,0.0003792728,0.00001762929,0.00009679451,0.00006208866,0.0004217558,0.9638857,0.001322474,0.0007822994,0.03287331],"study_design_scores_gemma":[0.000006334118,0.0001926401,0.0007494634,0.00006375161,0.00002321117,0.0003684595,0.00004008473,0.001885065,0.9345651,0.00060537,0.06147836,0.00002224989],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1443312,0.07661443,0.7330647,0.002893914,0.001998144,0.0009180947,0.001799192,0.002075432,0.03630487],"genre_scores_gemma":[0.3316089,0.07919081,0.4927284,0.001542382,0.0005963994,0.0008164562,0.001810201,0.0004103176,0.09129611],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002159886,"threshold_uncertainty_score":0.007225573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02368792969073621,"score_gpt":0.3319631901636174,"score_spread":0.3082752604728812,"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."}}