{"id":"W2142632334","doi":"10.1373/clinchem.2005.064758","title":"Fast In Vivo Microextraction: A New Tool for Clinical Analysis","year":2006,"lang":"en","type":"article","venue":"Clinical Chemistry","topic":"Analytical chemistry methods development","field":"Chemistry","cited_by":109,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Chromatography; Solid-phase microextraction; In vivo; Chemistry; Sample preparation; Extraction (chemistry); Detection limit; Pharmacokinetics; Mass spectrometry; Pharmacology; Gas chromatography–mass spectrometry; Medicine","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":[0.003043312,0.0008901432,0.0008640429,0.001200661,0.000212998,0.0009775702,0.000697202,0.001177593,0.00242491],"category_scores_gemma":[0.002573636,0.0003642618,0.0003404364,0.0005076632,0.001094811,0.001393526,0.0005502792,0.001863751,0.00113793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003659956,"about_ca_system_score_gemma":0.0006104503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001839539,"about_ca_topic_score_gemma":0.0003289447,"domain_scores_codex":[0.9986196,0.0005284988,0.00006740932,0.0002228434,0.0005209785,0.00004078495],"domain_scores_gemma":[0.9977224,0.0009197819,0.0004785353,0.0002808447,0.0004442236,0.0001541437],"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":[0.000862034,0.000297286,0.004806824,0.0009766518,0.00007752411,0.0004773435,0.0001444583,0.0004941179,0.6023983,0.003725854,0.005929033,0.3798106],"study_design_scores_gemma":[0.0006354654,0.008956864,0.02363362,0.0006295997,0.0004633177,0.02832582,0.0002260834,0.0197597,0.6105407,0.01318467,0.2933472,0.0002968957],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05045611,0.08257409,0.8475876,0.008727315,0.001518421,0.0005035834,0.0005073515,0.001802557,0.006323044],"genre_scores_gemma":[0.2212647,0.04472444,0.718797,0.004228683,0.002519435,0.0006197891,0.0005183352,0.0002894441,0.007038106],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003043312,"threshold_uncertainty_score":0.01609474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08083979737304275,"score_gpt":0.4245738044553417,"score_spread":0.3437340070822989,"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."}}