{"id":"W3208870411","doi":"10.1021/acsenvironau.1c00024","title":"<i>In Vivo</i> Solid-Phase Microextraction and Applications in Environmental Sciences","year":2021,"lang":"en","type":"review","venue":"ACS Environmental Au","topic":"Advanced Chemical Sensor Technologies","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Environment Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Solid-phase microextraction; In vivo; Chromatography; Materials science; Sample preparation; Chemistry; Nanotechnology; Environmental chemistry; Biomedical engineering; Gas chromatography–mass spectrometry; Mass spectrometry; Biology; Biotechnology","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":[0.000434483,0.000726193,0.0006358917,0.001523749,0.0001988272,0.0007893016,0.0005579609,0.0008268929,0.004462648],"category_scores_gemma":[0.0003764478,0.0001881697,0.0003843327,0.002083717,0.0004307613,0.001263917,0.0005668054,0.001419058,0.003805678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005032394,"about_ca_system_score_gemma":0.0006392493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009931793,"about_ca_topic_score_gemma":0.00216508,"domain_scores_codex":[0.9998631,0.00001826005,0.0000097428,0.00002688406,0.00006307536,0.0000188087],"domain_scores_gemma":[0.9998003,0.00008012012,0.00002645273,0.00001058332,0.00006573855,0.00001680518],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004514636,0.00005318902,0.0001250411,0.01104698,0.00004654593,0.0001250814,0.00003383729,0.0003871834,0.01491526,0.006578612,0.03984829,0.9267949],"study_design_scores_gemma":[0.000004986093,0.0000704244,0.0004228588,0.0009933835,0.00003146539,0.0005001221,0.0000249814,0.0001046707,0.004276403,0.001974992,0.991581,0.0000147395],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002906774,0.9929305,0.0007406511,0.000512864,0.0005615085,0.000007908448,0.00005983714,0.00002535617,0.004870584],"genre_scores_gemma":[0.001999023,0.9933358,0.0007479183,0.000484451,0.0002962014,0.00001205145,0.00009844529,0.000005876264,0.003020109],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004462648,"threshold_uncertainty_score":0.01492906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01517480744687941,"score_gpt":0.2998360858903259,"score_spread":0.2846612784434465,"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."}}