{"id":"W2313435125","doi":"10.1021/ac500801v","title":"Development of Needle Trap Technology for On-Site Determinations: Active and Passive Sampling","year":2014,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Analytical chemistry methods development","field":"Chemistry","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Chemistry; Sorbent; Sampling (signal processing); Passive sampling; Frit; Divinylbenzene; Desorption; Analytical Chemistry (journal); Chromatography; Polymer; Adsorption; Composite material; Materials science; Filter (signal processing); Styrene","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001627021,0.0002882181,0.000467645,0.00006180723,0.0001312971,0.00002021468,0.000251553,0.00036822,0.0002752705],"category_scores_gemma":[0.001424236,0.0002837508,0.000112899,0.0002180018,0.0002755823,0.00004036419,0.0001234417,0.000302446,0.000006159074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001520779,"about_ca_system_score_gemma":0.0001242245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.598878e-7,"about_ca_topic_score_gemma":5.593324e-7,"domain_scores_codex":[0.9982018,0.000006728708,0.0005741399,0.0005523461,0.0002677002,0.0003972501],"domain_scores_gemma":[0.9982817,0.0007577363,0.0001953111,0.000361151,0.000201565,0.0002025283],"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":[0.0001864634,0.0003165944,0.0007724954,0.001452159,0.0003666223,0.00000392987,0.0003916374,0.00001163736,0.8571556,0.002139924,0.0000842821,0.1371187],"study_design_scores_gemma":[0.0006374008,0.00001512963,0.00007047264,0.0001446896,0.00008902484,0.000009015101,0.0004813448,0.003574246,0.9825384,0.001854007,0.01025299,0.000333269],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8659693,0.00003050778,0.105308,0.0006861261,0.00002232433,0.0001415048,0.00005587126,0.0001417722,0.02764462],"genre_scores_gemma":[0.8546792,0.000006701141,0.1435753,0.00006594374,0.00009954419,0.00009273154,0.00006695564,0.00003697355,0.001376665],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1367854,"threshold_uncertainty_score":0.9999614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03486883435830188,"score_gpt":0.3196351395013186,"score_spread":0.2847663051430167,"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."}}