MétaCan
Menu
Back to cohort
Record W2996768505 · doi:10.1021/acs.analchem.9b04737

Requirements for Chromium Reactors for Use in the Determination of H Isotopes in Compound-Specific Stable Isotope Analysis of Chlorinated Compounds

2020· article· en· W2996768505 on OpenAlexafffund
Tetyana Gilevska, Ann Ojeda, Julian Renpenning, Steffen Kümmel, Matthias Gehre, Ivonne Nijenhuis, Barbara Sherwood Lollar

Bibliographic record

VenueAnalytical Chemistry · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaBundesministerium für Bildung und Forschung
KeywordsChemistryChromiumIsotope analysisHydrogenIsotopeElemental analysisStable isotope ratioAnalytical Chemistry (journal)Environmental chemistryInorganic chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

There is a strong need for careful quality control in hydrogen compound-specific stable isotope analysis (CSIA) of halogenated compounds. This arises in part due to the lack of universal design of the chromium (Cr) reactors. In this study, factors that optimize the critical performance parameter, linearity, for the Cr reduction method for hydrogen isotope analysis were identified and evaluated. These include the effects of short and long vertically mounted reactors and temperature profiles on trapping of Cl to ensure accurate and precise hydrogen isotope measurements. This paper demonstrates the critical parameters that need consideration to optimize any Cr reactor applications to ensure the accuracy of δ 2 H analysis for organic compounds and to enhance intercomparability for both international standards and reference materials run by continuous flow versus an elemental analyzer.

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)0.012
metaresearch head score (Gemma)0.021
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: Methods · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0040.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.003

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 head0.052
GPT teacher head0.287
Teacher spread0.235 · 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
GenreMethods

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

Citations12
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueAnalytical ChemistrySame topicIsotope Analysis in EcologyFrench-language works237,207