{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00003776007,0.0003342522,0.0005997287,0.0001379834,0.0000582542,0.00001774816,0.0002051559,0.0002686042,0.00006073081],"category_scores_gemma":[0.000004724712,0.0003356175,0.00007508441,0.000171014,0.0003647783,0.0001764823,0.0001440001,0.0004115064,0.0000318183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008620377,"about_ca_system_score_gemma":0.000004909219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005286603,"about_ca_topic_score_gemma":0.000007158178,"domain_scores_codex":[0.9986917,0.0000177089,0.0003842124,0.0004489129,0.0001290723,0.0003284056],"domain_scores_gemma":[0.9995688,0.00009037272,0.00006883916,0.0002248595,1.885214e-7,0.00004700276],"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":[0.000001081691,0.0004059159,0.0001363257,0.001241856,0.00003831312,0.00005697904,0.00006170048,0.000504781,0.1219876,0.0000453883,0.00008319417,0.8754368],"study_design_scores_gemma":[0.0002315272,0.00002101064,0.000009446555,0.0005503955,0.00005190012,0.00006534363,0.0002229732,0.00002992428,0.02721626,0.00008030182,0.9710648,0.0004561345],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01572002,0.9832915,0.00005738917,0.000006137996,0.0000458189,0.0004656044,0.0001439844,0.00007291319,0.000196631],"genre_scores_gemma":[0.01256448,0.9867874,0.0002022034,0.000009986381,0.00003699417,0.0002115944,0.00008449691,0.0000438975,0.00005892801],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9709816,"threshold_uncertainty_score":0.9999096,"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."}}