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Record W2091074275 · doi:10.1021/ac026260b

Improved Sensitivity and Characterization of High-Speed Ion Chromatography of Inorganic Anions

2003· article· en· W2091074275 on OpenAlexafffund
Panos Hatsis, Charles A. Lucy

Bibliographic record

VenueAnalytical Chemistry · 2003
Typearticle
Languageen
FieldChemistry
TopicAnalytical Chemistry and Chromatography
Canadian institutionsAlberta Glycomics CentreUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryIodateBromideBromateSulfateChromatographyNitriteNitrateDetection limitChlorideIon chromatographyPhosphateIodideThermal conductivity detectorConductivityAnalytical Chemistry (journal)Inorganic chemistryGas chromatographyOrganic chemistry

Abstract

fetched live from OpenAlex

In this work, a reversed-phase monolithic column was permanently coated with didodecyldimethylammonium bromide (DDAB) to perform ultrafast separations of iodate, chloride, nitrite, bromide, nitrate, phosphate, and sulfate in as little as 30 s. Separations were performed using 6 mM o-cyanophenol (pH 7.0) at flow rates up to 10 ml/min and suppressed conductivity detection. Detection limits in the parts-per-billion range were observed for all anions studied (e.g., ranging from 30 ppb for phosphate to 4 ppb for sulfate). The reproducibility was 0.7 and 0.4% RSD for retention time and peak area, respectively. Coated columns were stable for up to 12 h of continuous use at 5 mL/min (i.e., 1-min separations).

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.006
GPT teacher head0.206
Teacher spread0.200 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations83
Published2003
Admission routes2
Has abstractyes

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