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Record W4382981940 · doi:10.1029/2023gb007759

Remote Sensing Soil Freeze‐Thaw Status and North American N <sub>2</sub> O Emissions From a Regional Inversion

2023· article· en· W4382981940 on OpenAlexaboutno aff
C. D. Nevison, Xin Lan, Stephen M. Ogle

Bibliographic record

VenueGlobal Biogeochemical Cycles · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceGrowing seasonNitrous oxideFertilizerAtmospheric sciencesInversion (geology)NitrogenSeasonalityAnnual cycleClimatologyAgronomyHydrology (agriculture)EcologyChemistryGeologyBiology

Abstract

fetched live from OpenAlex

Abstract North American nitrous oxide (N 2 O) emissions over 2011–2018 are estimated using the CarbonTracker‐Lagrange regional inversion framework. Emissions are strongest in the Midwestern corn/soybean belt and display a distinct dual maxima seasonal pattern. The first maximum occurs in late winter/early spring, suggestive of freeze‐thaw (FT) effects on denitrification rates and associated N 2 O emissions. The second maximum occurs in late spring/early summer, consistent with a growing season nitrogen fertilizer‐driven source, although fertilizer applied in late fall may contribute to the FT pulse as well. Interannual variability in the first maximum correlates significantly to soil freeze thaw status derived from remote sensing data. A requisite frozen period in the preceding early winter appears necessary to create conditions for the N 2 O pulse after thawing. The FT pulse is a prominent feature of the annual cycle in Canadian cropland, where it may be of comparable magnitude to growing season emissions. In contrast, the growing season peak in N 2 O dominates the FT peak in the Midwestern Corn‐Soybean region of the United States.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score0.929

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.029
GPT teacher head0.236
Teacher spread0.207 · 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 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

Citations11
Published2023
Admission routes1
Has abstractyes

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