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Record W3206916838 · doi:10.5281/zenodo.4632428

Year 2020 reservoir methane and CO2 emissions as predicted by the g-res model

2021· dataset· en· W3206916838 on OpenAlexaff
John A. Harrison, Yves T. Prairie, Sara Mercier‐Blais, Cynthia Soued

Bibliographic record

VenueFigshare · 2021
Typedataset
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsMethaneMethane emissionsEnvironmental scienceGreenhouse gasAtmospheric sciencesGeologyChemistryOceanography

Abstract

fetched live from OpenAlex

This dataset accompanies the following publication: Harrison, J.A., Y.T. Prairie, S. Mercier-Blais, and C. Soued, (2021) Year-2020 Global Distribution and Pathways of Reservoir Methane and Carbon Dioxide Emissions According to the Greenhouse Gas from Reservoirs (G-res) Model, <em>Global Biogeochemical Cycles.</em> It includes year 2020 estimates of methane and CO<sub>2</sub> emissions from reservoirs on a per-reservoir surface area basis and on a per-one-degree by one-degree cell basis. Data are provided in tabular format for latitudinal distribution by flux pathway and in gridded ASCII format for total CH<sub>4</sub> plus CO<sub>2</sub> fluxes. Tabular GHG flux estimates by latitude include fluxes only from reservoirs in the G-res Database (Prairie et al., 2021) and must be multiplied by an "area correction factor" (1.47) to match values in Harrison et al. (2021). Flux estimates in the gridded datasets do not require such correction.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.297
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.2980.001

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 head0.014
GPT teacher head0.234
Teacher spread0.220 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2021
Admission routes1
Has abstractyes

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