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Record W2940563241 · doi:10.1002/rcm.8470

<sup>17</sup> O‐excess as a detector for co‐extracted organics in vapor analyses of plant isotope signatures

2019· article· en· W2940563241 on OpenAlexaff
Magali F. Nehemy, Cody Millar, Kim Janzen, Marcel Gaj, Dyan Pratt, Colin P. Laroque, Jeffrey J. McDonnell

Bibliographic record

VenueRapid Communications in Mass Spectrometry · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsGlobal Institute for Water SecurityUniversity of Saskatchewan
Fundersnot available
KeywordsEnvironmental chemistryIsotopeDetectorAnalytical Chemistry (journal)RadiochemistryChemistryEnvironmental sciencePhysicsNuclear physicsOptics

Abstract

fetched live from OpenAlex

Rationale The stable isotope compositions of hydrogen and oxygen in water (δ 2 H and δ 18 O values) have been widely used to investigate plant water sources, but traditional isotopic measurements of plant waters are expensive and labor intensive. Recent work with direct vapor equilibration (DVE) on laser spectroscopy has shown potential to side step limitations imposed by traditional methods. Here, we evaluate DVE analysis of plants with a focus on spectral contamination introduced by organic compounds. We present 17 O‐excess as a way of quantifying organic compound interference in DVE. Methods We performed isotopic analysis using the δ 2 H, δ 18 O and δ 17 O values of water on an Off‐Axis Integrated Cavity Output Spectroscopy (IWA‐45EP OA‐ICOS) instrument in vapor mode. We used a set of methanol (MeOH) and ethanol (EtOH) solutions to assess errors in isotope measurements. We evaluated how organic compounds affect the 17 O‐excess. DVE was used to measure the isotopic signatures in natural plant material from Pinus banksiana , Picea mariana , and Larix laricina , and soil from boreal forest for comparison with solutions. Results The 17 O‐excess was sensitive to the presence of organic compounds in water. 17 O‐excess changed proportionally to the concentration of MeOH per volume of water, resulting in positive values, while EtOH solutions resulted in smaller changes in the 17 O‐excess. Soil samples did not show any spectral contamination. Plant samples were spectrally contaminated on the narrow‐band and were enriched in 1 H and 16 O compared with source water. L. laricina was the only species that did not show any evidence of spectral contamination. Xylem samples that were spectrally contaminated had positive 17 O‐excess values. Conclusions 17 O‐excess can be a useful tool to identify spectral contamination and improve DVE plant and soil analysis in the laboratory and in situ . The 17 O‐excess flagged the presence of MeOH and EtOH. Adding measurement of δ 17 O values to traditional measurement of δ 2 H and δ 18 O values may shed new light on plant water analysis for source mixing dynamics using DVE.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.322
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.022
GPT teacher head0.310
Teacher spread0.287 · 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 designObservational
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

Citations37
Published2019
Admission routes1
Has abstractyes

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