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Record W2064557254 · doi:10.4141/s00-032

Carbon dioxide balance of a crop-fallow rotation in western Canada

2001· article· en· W2064557254 on OpenAlexvenueaboutno aff
S. M. McGinn, O. O. Akinremi

Bibliographic record

VenueCanadian Journal of Soil Science · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsCarbon dioxideCrop rotationEnvironmental scienceSummer fallowAgronomySoil respirationCropSoil waterAtmosphere (unit)ChemistryAgricultureSoil scienceBiologyGeographyEcology

Abstract

fetched live from OpenAlex

The use of micrometeorological and chamber techniques is a unique means to investigate the seasonal CO2 cycle in agriculture. Two growing seasons are reported in this study, one being a wet year (207 mm 1994) and the other a dry year (86 mm 1996). A Bowen ratio tower and automated soil chambers were set up in a barley and fallow field to simultaneously monitor energy and carbon dioxide fluxes. These fluxes were integrated over the measurement period to arrive at a seasonal carbon balance of each surface. Our results show that barley removed CO2 from the atmosphere, amounting to −9.5 and −8.5 Mg CO2 ha-1 in 1994 and 1996, respectively. A portion of the atmospheric CO2 was retained by the soil (6.6 and 3.7 Mg CO2 ha-1 in 1994 and 1996, respectively). The soil in fallow emitted −11.1 and −6.7 Mg CO2 ha-1 in 1994 and 1996, respectively. Above a crop-fallow area, the atmosphere gained CO2 from the surface in 1994 (0.8 Mg CO2 ha-1) but was a source of CO2 in 1996 (losing −1 Mg CO2 ha-1 to the surface). The soil under a crop-fallow area lost CO2 in both years (−2.2 and −1.5 Mg CO2 ha-1 in 1994 and 1996, respectively). Key words: Carbon dioxide, fluxes, barley, fallow, respiration, photosynthesis

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.177
Teacher spread0.172 · 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 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

Citations13
Published2001
Admission routes2
Has abstractyes

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Same venueCanadian Journal of Soil ScienceSame topicPlant Water Relations and Carbon DynamicsFrench-language works237,207