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Record W2060030736 · doi:10.1039/c002360d

Thin film hydride generation: determination of ultra-trace copper by flow injection in situ hydride trapping graphite furnace AAS

2010· article· en· W2060030736 on OpenAlexaff
Chengbin Zheng, Ralph E. Sturgeon, Xiandeng Hou

Bibliographic record

VenueJournal of Analytical Atomic Spectrometry · 2010
Typearticle
Languageen
FieldChemistry
TopicAnalytical chemistry methods development
Canadian institutionsNational Research Council Canada
FundersSichuan UniversityNational Natural Science Foundation of China
KeywordsHydrideCopperGraphiteSeparator (oil production)ChemistryDetection limitAnalytical Chemistry (journal)AnalyteFormic acidNitric acidCertified reference materialsChromatographyInorganic chemistryHydrogen

Abstract

fetched live from OpenAlex

A novel system which significantly enhances copper hydride generation efficiency was used for the determination of trace copper by coupling a flow injection system to a graphite furnace for in situ collection of the analyte and subsequent AAS detection. A single device integrated the functions of hydride generator and gas liquid separator. Solutions of the sample containing 0.0005% (m/v) phenanthroline and 1% formic acid were merged with tetrahydroborate reductant to yield a thin film wetting a reaction surface from which product vapor was efficiently liberated and transported to the heated furnace. Optimum operating conditions provided for a generation/transport/collection efficiency of 8–12%. Interferences from common transition and noble metals were effectively eliminated. A limit of detection of 100 pg ml−1 was obtained based on processing a 1 ml sample volume. A precision of better than 4% (RSD) at 1 ng ml−1 was typical. The methodology was successfully applied to the determination of Cu in several NRCC natural water and biological tissue Certified Reference Materials.

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.

How this classification was reachedexpand

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.057
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.273
Teacher spread0.260 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations34
Published2010
Admission routes1
Has abstractyes

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