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Record W2784720411 · doi:10.3334/ornldaac/1402

CARVE: L2 Merged Atmospheric CO2, CO, O3 and CH4 Concentrations, Alaska, 2012-2015

2016· article· en· W2784720411 on OpenAlexaboutno aff
J. Budney, Rachel Y-W Chang, R. Commane, B. C. Daube, Archana Dayalu, S. J. Dinardo, E. W. Gottlieb, A. Karion, Jakob Lindaas, Charles E. Miller, J. B. Miller, Scot M. Miller, M. Pender, J. V. Pittman, Jenna Samra, Colm Sweeney, Steven C. Wofsy, Bo Xiang

Bibliographic record

VenueOak Ridge National Laboratory Distributed Active Archive Center for Biogeochemical Dynamics · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceAtmospheric sciencesMeteorologyClimatologyGeologyGeography

Abstract

fetched live from OpenAlex

This data set provides atmospheric carbon dioxide (CO2), methane (CH4), carbon monoxide (CO), ozone (O3), and water vapor (H2O) concentrations from airborne campaigns over the Alaskan and Canadian arctic for the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE). These data are merged and gap-filled outputs from two different cavity ring-down spectrometers (CRDS; Picarro Inc.) flown aboard the CARVE aircraft and are presented at 5-second intervals throughout each flight. Aircraft latitude, longitude, and altitude are also provided. Flight campaigns took place from 2012 to 2015 between the months of March and November to enable investigation of both seasonal and inter-annual variability in atmospheric gas content. The measurements included in this data set are crucial for understanding changes in Arctic carbon cycling and the potential threats posed by thawing of Arctic permafrost.

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: Dataset · Consensus signal: none
Teacher disagreement score0.153
Threshold uncertainty score0.305

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.005
GPT teacher head0.224
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; 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
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

Citations5
Published2016
Admission routes1
Has abstractyes

Explore more

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