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AN ANALYTICAL MODEL OF SOIL ORGANIC CARBON DYNAMICS BASED ON A SIMPLE "HOCKEY STICK" FUNCTION

2001· article· en· W2327547389 on OpenAlexaff
Yongsheng Feng, Xiaomei Li

Bibliographic record

VenueSoil Science · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsAlberta Environment and Protected AreasUniversity of Alberta
Fundersnot available
KeywordsSoil carbonResidue (chemistry)NitrogenCarbon fibersTotal organic carbonSoil waterChemistryFunction (biology)Soil scienceEnvironmental chemistryMathematicsEnvironmental scienceOrganic chemistry

Abstract

fetched live from OpenAlex

We developed a simple analytical model for carbon and nitrogen dynamics in soils. Description of the soil C and N dynamics focus on the total carbon residue function, R, defined as the fraction of original plant carbon input remaining in the soil as a function of time, and nitrogen concentration function, N, defined as the N concentration of the carbon residue as a function of R. A simple two-parameter function, R = Exp(−(kt)α), was used for total carbon residue function. N concentration of carbon residue is derived to be a linear function of R. We tested our model with data reported in the literature. The model parameters (k and α) were calculated from independently determined gross turnover time and 14C age of soil organic carbon. Our model accurately predicts C and N dynamics in response to fertilization and manure application for time periods ranging from a few months to more than 150 years.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.020
GPT teacher head0.237
Teacher spread0.216 · 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 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

Citations29
Published2001
Admission routes1
Has abstractyes

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