{"id":"W4412035281","doi":"10.46770/as.2025.067","title":"A Miniature Purge-and-Trap Using a Gold-plated Wire for Field Detection of Ultra-Trace Mercury in Water by Microplasma Optical Emission Spectrometry","year":2025,"lang":"en","type":"article","venue":"Atomic Spectroscopy","topic":"Analytical chemistry methods development","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Research Council Canada; Fundamental Research Funds for the Central Universities; Sichuan University; Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Mercury (programming language); Microplasma; Chemistry; Mass spectrometry; Trap (plumbing); Analytical Chemistry (journal); Purge; Environmental chemistry; Chromatography; Plasma; Waste management; Environmental engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000276726,0.0003021891,0.0005125685,0.0001338037,0.00006113781,0.0000301529,0.0001936119,0.0004287052,0.0001723907],"category_scores_gemma":[0.0002565308,0.0002657626,0.0001287223,0.0003133929,0.00008746491,0.00006553953,0.0000561014,0.0004984924,0.000001595828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003789654,"about_ca_system_score_gemma":0.0001009239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003503461,"about_ca_topic_score_gemma":0.000005824453,"domain_scores_codex":[0.9981363,0.00002509388,0.0005761596,0.0005674671,0.000176085,0.0005188557],"domain_scores_gemma":[0.999065,0.0003840791,0.000100868,0.000283376,0.00005063202,0.0001160485],"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":[0.0004976395,0.0001012487,0.001586662,0.00042259,0.00009805181,0.000007420031,0.00008884146,9.775333e-7,0.9963716,0.00002734278,0.0003106602,0.0004869288],"study_design_scores_gemma":[0.00104499,0.0000345555,0.00007113814,0.0002446533,0.0000999921,0.00002970337,0.0001226111,0.001432436,0.9951752,0.0007832129,0.0006918097,0.0002697309],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9776531,0.0004989027,0.01998218,0.0005113338,0.00008553552,0.0001702401,0.00001535383,0.00004896403,0.001034336],"genre_scores_gemma":[0.9659182,0.00007127789,0.03285722,0.00009729833,0.0000429983,0.00002022129,0.00002551676,0.00003096415,0.000936306],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01287503,"threshold_uncertainty_score":0.9999794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00866577736361325,"score_gpt":0.2856939123482417,"score_spread":0.2770281349846285,"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."}}