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Record W271912962 · doi:10.3334/ornldaac/310

BOREAS TE-01 CH4 Flux Data over the SSA-OA

2012· dataset· en· W271912962 on OpenAlexaff
D. W. Anderson

Bibliographic record

VenueNASA Technical Reports Server (NASA) · 2012
Typedataset
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsTransectOak Ridge National LaboratoryMethaneEnvironmental scienceFlux (metallurgy)Soil waterSampling (signal processing)SeasonalityRidgeHydrology (agriculture)Atmospheric sciencesSoil scienceChemistryEcologyGeographyGeologyOceanographyCartography

Abstract

fetched live from OpenAlex

The BOREAS TE-1 team collected various data to characterize the soil-plant systems in the BOREAS SSA. Particular emphasis was placed on nutrient biochemistry, the stores and transfers of organic carbon, and how the characteristics were related to measured methane fluxes. The overall transect in the Prince Albert National Park (Saskatchewan, Canada) included the major plant communities and related soils that occurred in that section of the boreal forest. Soil physical, chemical, and biological measurements along the transect were used to characterize the static environment, which allowed them to be related to methane fluxes. Chamber techniques were used to provide a measure of methane production/uptake. Chamber measurements coupled with flask sampling were used to determine the seasonality of methane fluxes. This particular data set contains methane flux and soil profile methane concentration values from the SSA-OA site. The data were collected from 29-May to 17-Sep-1994. The data are stored in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.087
Threshold uncertainty score0.173

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0200.018

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 head0.019
GPT teacher head0.260
Teacher spread0.241 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2012
Admission routes1
Has abstractyes

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