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Record W2781605240 · doi:10.1021/acs.analchem.7b04376

Low-Temperature and Atmospheric Pressure Sample Digestion Using Dielectric Barrier Discharge

2018· article· en· W2781605240 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnalytical Chemistry · 2018
Typearticle
Languageen
FieldMedicine
TopicPlasma Applications and Diagnostics
Canadian institutionsNational Research Council Canada
FundersNational Natural Science Foundation of China
KeywordsChemistryAtmospheric pressureDielectric barrier dischargeDigestion (alchemy)DielectricSample (material)Analytical Chemistry (journal)Environmental chemistryChromatographyOptoelectronicsMeteorology

Abstract

fetched live from OpenAlex

A new sample digestion method using a double layer and coaxial dielectric barrier discharge (DBD) digestion reactor was developed for the sensitive determination of trace elements in rice samples. All the operation parameters of the DBD microplasma and other digestion conditions were carefully optimized. Three DBD-digestion modes were investigated for real matrix samples, including H 2 O-DBD-digestion, H 2 O 2 -DBD-digestion, and HNO 3 -DBD-digestion systems. Among the three modes, the H 2 O-DBD-digestion system provides a suitable digestion of sample without any additional chemicals, achieving environmental friendly sample treatment and eliminating the potential interferences. Under the optimized conditions, limits of detection for Mg, Mn, Zn, Cd, Cr, Co, and As were in the range of 0.01–0.35 ng g –1 by inductively coupled plasma mass spectrometry (ICPMS). The accuracy of the proposed method was checked by analysis of a certified reference material (GBW10043) and spiked samples with satisfactory results (83–113% recoveries).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.161
Threshold uncertainty score0.401

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.263
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it