{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002625065,0.0001987759,0.0007506539,0.0004079938,0.0002681692,0.00001398419,0.0002123953,0.000745064,0.0005699019],"category_scores_gemma":[0.0001575937,0.0001848569,0.0003421677,0.000177705,0.0002144741,0.000116679,0.00002910416,0.0001581495,0.000003755938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002490992,"about_ca_system_score_gemma":0.00004929811,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008510825,"about_ca_topic_score_gemma":0.006418031,"domain_scores_codex":[0.9990253,0.0001293958,0.0002180726,0.0003851056,0.00004145286,0.0002006119],"domain_scores_gemma":[0.9986048,0.0002307322,0.000662418,0.0002443463,0.0002323382,0.00002538633],"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":[0.004561752,0.000305043,0.0007247569,0.0001867687,0.003746604,0.000002218912,0.005999854,0.000003012813,0.9761123,0.0001173182,0.000943522,0.007296816],"study_design_scores_gemma":[0.006207763,0.003865461,0.02912436,0.0001905533,0.01717219,0.000006868238,0.03330368,0.0006183704,0.8916261,0.0008431671,0.01603143,0.00101003],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971434,0.0007536538,0.0003289333,0.0001452858,0.0001989342,0.0003955589,0.0009627909,0.00002104321,0.00005039333],"genre_scores_gemma":[0.8275828,0.00150476,0.009339164,0.00002494938,0.00002915014,0.000003523984,0.01329851,0.0000218454,0.1481953],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1695606,"threshold_uncertainty_score":0.9980916,"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."}}