{"id":"W2011240030","doi":"10.1016/j.microc.2013.01.006","title":"Mercury species determination by task specific ionic liquid-based ultrasound-assisted dispersive liquid–liquid microextraction combined with cold vapour generation atomic absorption spectrometry","year":2013,"lang":"en","type":"article","venue":"Microchemical Journal","topic":"Analytical chemistry methods development","field":"Chemistry","cited_by":93,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Research Council Canada; Politechnika Poznańska","keywords":"Chemistry; Detection limit; Ionic liquid; Cold vapour atomic fluorescence spectroscopy; Chromatography; Certified reference materials; Mercury (programming language); Extraction (chemistry); Atomic absorption spectroscopy; Aqueous two-phase system; Tap water; Analytical Chemistry (journal); Aqueous solution; Ionic strength; Sample preparation; Solvent","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000406292,0.0006779202,0.0006254425,0.0001953487,0.0004253144,0.0004315721,0.000516326,0.0005477921,0.005602429],"category_scores_gemma":[0.0001984359,0.0006274578,0.0003188709,0.0004246711,0.0002957441,0.0004976172,0.00006633801,0.001350477,0.0001958243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0024323,"about_ca_system_score_gemma":0.0002929464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001244571,"about_ca_topic_score_gemma":0.000002750502,"domain_scores_codex":[0.996201,0.0001274243,0.001123705,0.0008369523,0.0008533274,0.000857626],"domain_scores_gemma":[0.9972434,0.0003377144,0.0007673761,0.0004640784,0.0006316399,0.0005557691],"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":[0.001650208,0.0004856752,0.00008487986,0.00008351541,0.0001685047,0.00003192115,0.00007121255,0.00000944942,0.9896197,0.00001300004,0.007646304,0.0001356304],"study_design_scores_gemma":[0.002213263,0.0004567049,0.00009372032,0.000173522,0.0001697535,0.0008047808,0.000243969,0.000368762,0.9908233,0.00001710123,0.00384668,0.0007884579],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.933157,0.0003814902,0.06454389,0.0008038325,0.0001565936,0.0002450691,0.0000445366,0.0001200412,0.0005474969],"genre_scores_gemma":[0.9699068,0.0002824271,0.02653464,0.0002817498,0.0008758204,0.00005820315,0.0006780135,0.0001082295,0.001274134],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03800925,"threshold_uncertainty_score":0.9996177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01387331466073593,"score_gpt":0.2373401492247232,"score_spread":0.2234668345639872,"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."}}