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Record W2276168176 · doi:10.1002/eco.1722

Critical issues with cryogenic extraction of soil water for stable isotope analysis

2015· article· en· W2276168176 on OpenAlexaff
Natalie Orlowski, Lutz Breuer, Jeffrey J. McDonnell

Bibliographic record

VenueEcohydrology · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGroundwater and Isotope Geochemistry
Canadian institutionsGlobal Institute for Water SecurityUniversity of Saskatchewan
Fundersnot available
KeywordsExtraction (chemistry)Water extractionEnvironmental scienceSoil waterIsotope analysisEcohydrologyEnvironmental chemistryGroundwaterFraction (chemistry)Soil scienceChemistryEcosystemGeologyGeotechnical engineeringChromatographyEcology

Abstract

fetched live from OpenAlex

Abstract Cryogenic water extraction is the most widely used method to facilitate the laboratory removal of soil pore water for isotopic analysis. However, recent studies have suggested that cryogenic extraction conditions (extraction time, temperature, vacuum threshold) and physicochemical soil properties can influence extracted water isotopic signatures. Here, we argue that new work is needed to analyse the full extent of these effects on the extracted water isotopic composition. We illustrate this need with a simple lab experiment and show that in addition to extraction times, soil organic matter and its exchangeable bonded hydrogen fraction influence the resulting isotope composition. We hope these comments stimulate discussion on the assumptions and limitations of cryogenic extraction for soil water and lead ultimately to a standardization of testing approaches. © 2016 The Authors. Ecohydrology published by John Wiley & Sons Ltd.

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)0.041
metaresearch head score (Gemma)0.045
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 score0.041
Threshold uncertainty score0.217

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0410.045
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.006
Scholarly communication0.0030.004
Open science0.0040.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.002

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 head0.018
GPT teacher head0.256
Teacher spread0.238 · 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

Citations197
Published2015
Admission routes1
Has abstractyes

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