{"id":"W4281396668","doi":"10.1007/s00216-022-04129-w","title":"Comparison of four commercial solid-phase micro-extraction (SPME) fibres for the headspace characterisation and profiling of gunshot exhausts in spent cartridge casings","year":2022,"lang":"en","type":"article","venue":"Analytical and Bioanalytical Chemistry","topic":"Toxic Organic Pollutants Impact","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Canadian Mounted Police","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Cartridge; Polydimethylsiloxane; Ammunition; Chromatography; Solid-phase microextraction; Extraction (chemistry); Solid phase extraction; Chemistry; Materials science; Gas chromatography–mass spectrometry; Mass spectrometry; Composite material; Metallurgy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004072028,0.0001342574,0.0003330146,0.00002478031,0.0001218478,0.00001819537,0.0001236997,0.00006880782,0.0004741805],"category_scores_gemma":[0.0001656643,0.000104397,0.00007007027,0.0002204204,0.0003889804,0.00006981347,0.0001748342,0.0002286684,6.401397e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001203045,"about_ca_system_score_gemma":0.00002253165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001044708,"about_ca_topic_score_gemma":0.00002385603,"domain_scores_codex":[0.9987448,0.0000319137,0.0004341913,0.0002627647,0.0002818853,0.0002444275],"domain_scores_gemma":[0.9992787,0.0002916638,0.0001604807,0.0001518975,0.000005652337,0.0001116317],"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":[0.0004799931,0.0005427223,0.07743092,0.00008611907,0.00005749745,0.00000651611,0.0003138684,0.00004772286,0.9057096,0.00002574185,0.0001851439,0.0151142],"study_design_scores_gemma":[0.001421694,0.0003055345,0.1972147,0.00002312595,0.000223964,0.00006045508,0.0009853436,0.0799479,0.7190055,0.0001006947,0.000473899,0.0002371808],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975872,0.0000659852,0.0001933828,0.0016739,0.00002155771,0.0001973158,0.0001181988,0.000005317852,0.000137126],"genre_scores_gemma":[0.9996288,0.00001416017,0.0001528644,0.00005619,0.00003611499,0.000005047622,0.000009860368,0.000008149276,0.00008884724],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1867041,"threshold_uncertainty_score":0.5191944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04272563735796558,"score_gpt":0.3678135692888613,"score_spread":0.3250879319308957,"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."}}