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Record W1493509693 · doi:10.1002/2014gl062768

Long‐term change of CO<sub>2</sub> latitudinal distribution in the upper troposphere

2015· article· en· W1493509693 on OpenAlexfundno aff
Hidekazu Matsueda, Toshinobu Machida, Yousuke Sawa, Yosuke Niwa

Bibliographic record

VenueGeophysical Research Letters · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
FundersMinistry of Education, IndiaMinistry of Education, Culture, Sports, Science and TechnologyYork University
KeywordsTroposphereSouthern HemisphereNorthern HemisphereClimatologyBiosphereEnvironmental scienceLatitudeAtmospheric sciencesBiosphere modelGeology

Abstract

fetched live from OpenAlex

Abstract We analyzed temporal variations in the annual mean latitudinal distribution of upper tropospheric CO 2 using the aircraft measurements taken between Japan and Australia over the period 1993–2013, plus earlier data from 1984 and 1985. The observed CO 2 latitudinal gradient between 30°N and 30°S showed large interannual variations that are clearly associated with El Niño–Southern Oscillation events. We also found long‐term increasing trends of the CO 2 gradients in the most northern latitudes that are proportionally associated with increasing fossil fuel emissions, while decreasing trends were found around the tropical regions. Extrapolation of the changes in the CO 2 gradient back to zero fossil fuel emissions showed a negative north‐south gradient with lower CO 2 in the Northern Hemisphere than in the Southern Hemisphere, as well as a regional CO 2 elevation in the tropical regions. These features provide a useful constraint on model estimates of CO 2 fluxes from the ocean and the land biosphere.

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 score0.029
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.038
GPT teacher head0.291
Teacher spread0.254 · 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

Citations38
Published2015
Admission routes1
Has abstractyes

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