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Record W1994461728 · doi:10.1021/ac991384i

On-Line D/H Analysis for Water, Natural Gas, and Organic Solvents by Manganese Reduction

2000· article· en· W1994461728 on OpenAlexafffund
Orfan Shouakar‐Stash, R.J. Drimmie, John E. Morrison, Shaun K. Frape, A. R. Heemskerk, William A. Mark

Bibliographic record

VenueAnalytical Chemistry · 2000
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaInternational Atomic Energy Agency
KeywordsChemistryManganeseMethaneBrineMass spectrometryHydrogenAnalytical Chemistry (journal)Sample preparationNatural gasTube (container)ChromatographyOrganic chemistryWaste management

Abstract

fetched live from OpenAlex

A new technique for on-line sample preparation and D/H determination is described. The technique is suitable for the preparation of fresh and brine waters, as well as natural gases and organic solvents. A 5-microL sample of water or hydrogen equivalent is injected and reduced by means of hot manganese metal in a specially designed reaction tube surrounded by a tube furnace and attached directly to the mass spectrometer inlet without modification.The hydrogen gas flows directly into the MS to be analyzed by reference/sample comparison. The reproducibility varied between 0.7 and 1.8% for all liquid and gas samples. The accuracy of this technique is confirmed by analysis of IAEA standard waters V-SMOW, GISP, and SLAP, as well as NGS-3 (IAEA methane intercomparison material).

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)0.000
metaresearch head score (Gemma)0.000
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: none
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.003

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 head0.264
Teacher spread0.255 · 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

Citations28
Published2000
Admission routes2
Has abstractyes

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