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Record W2149789227 · doi:10.1002/rcm.4189

A numerical evaluation of chamber methodologies used in measuring the <i>δ</i> <sup>13</sup> C of soil respiration

2009· article· en· W2149789227 on OpenAlexafffund
Nick Nickerson, D. A. Risk

Bibliographic record

VenueRapid Communications in Mass Spectrometry · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsSt. Francis Xavier University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryField (mathematics)Measure (data warehouse)MechanicsStatistical physicsPhysicsComputer scienceData mining

Abstract

fetched live from OpenAlex

Measurement of the delta(13)C value of soil-respired CO(2) (delta(r)) has become a commonplace method through which ecosystem function and C dynamics can be better understood. Despite its proven utility there is currently no consensus on the most robust method with which to measure delta(r). Static and dynamic chamber systems are both commonly used for this purpose; however, the literature on these methods provides evidence suggesting that measurements of delta(r) made with these chamber systems are neither repeatable (self-consistent) nor comparable across methodologies. Here we use a three-dimensional (3-D) numerical soil-atmosphere-chamber model to test these chamber systems in a 'surrogate reality'. Our simulations show that each chamber methodology is inherently biased and that no chamber methodology can accurately predict the true delta(r) signature under field conditions. If researchers intend to use delta(r) to study in situ ecosystem processes, the issues with these chamber systems need to be corrected either by using diffusive theory or by designing a new, unbiased delta(r) measurement system.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.431
Threshold uncertainty score0.446

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.073
GPT teacher head0.315
Teacher spread0.242 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations40
Published2009
Admission routes2
Has abstractyes

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