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Record W3106798036 · doi:10.1002/rcm.9008

Designing working standards for stable H, C, and O isotope measurements in CO <sub>2</sub> and H <sub>2</sub> O

2020· article· en· W3106798036 on OpenAlexaff
Jean‐François Hélie, Claude Hillaire‐Marcel

Bibliographic record

VenueRapid Communications in Mass Spectrometry · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsCarbonateChemistryStable isotope ratioCalibrationIsotopeSelection (genetic algorithm)Characterization (materials science)Stability (learning theory)Protocol (science)Isotope analysisMineralogyGeologyStatisticsComputer scienceNanotechnologyMaterials science

Abstract

fetched live from OpenAlex

RATIONALE: We address here the selection, preparation, calibration, storage, and use of carbonate and water working standards (WSs) for stable H, C, and O isotope measurements requiring the best possible precision and accuracy vs international reference materials (iRMs). This may be of interest for laboratories working intensively in the domains of the carbon and water cycles and of paleoclimate. METHODS: O values, respectively, are normally used. In both cases, a strict protocol must be followed to properly qualify the WS vs the current international isotopic scales, and much attention must be paid to calculating rigorous estimates of final uncertainties on these scales. RESULTS: Two specific protocols for the selection of carbonate and water WSs are detailed. Equations for a proper estimate of uncertainties are proposed. CONCLUSIONS: The selection of WSs involves a preselection of potentially suitable materials based on initial estimates of their mineralogical, chemical, and isotopic properties and long-term stability, based on literature or previous measurements. Their precise characterization vs international isotopic scales requires a thorough analytical work in a correct sequence. When properly carried out, the proposed protocols should permit WSs to be obtained, defined vs the VSMOW and VPDB scales, with uncertainties comparable with those achieved for the characterization of iRMs.

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)0.032
metaresearch head score (Gemma)0.032
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: Methods
Teacher disagreement score0.032
Threshold uncertainty score0.168

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.032
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0020.004
Scholarly communication0.0030.003
Open science0.0030.004
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0030.005

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 head0.043
GPT teacher head0.279
Teacher spread0.236 · 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

Citations8
Published2020
Admission routes1
Has abstractyes

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