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Record W4366263003 · doi:10.21203/rs.3.rs-2753938/v1

The 2010-15 anomaly in the Southern Hemisphere baseline CO2

2023· preprint· en· W4366263003 on OpenAlexfundno aff
R. J. Francey, Jorgen S. Frederiksen

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
FundersEnvironment and Climate Change CanadaAustralian Antarctic DivisionAustralian Institute of Marine Science
KeywordsAnomaly (physics)Southern HemisphereClimatologyEnvironmental scienceAtmospheric sciencesFlux (metallurgy)Baseline (sea)Northern HemisphereLatitudeMiddle latitudesGeologyPhysicsOceanographyChemistry

Abstract

fetched live from OpenAlex

Abstract The CO2 measured in baseline air collected over three decades from six Southern Hemisphere sites spanning 70° of latitude uniformly indicate an 11 PgC anomaly between 2010 and 2015. The anomaly, in annually averaged residuals from the smooth increase due to the cumulative total of long lived anthropogenic emissions, exceeds uptake expected from modelled sinks. It also departs from long term lagged correlations with ENSO indices. Air-surface exchange is of insufficient magnitude, abruptness, and persistence to explain the anomaly. Overestimation in the 3–4 PgC year− 1 interhemispheric flux of fossil emissions is implied. The anomaly trails the GFC, whose impact is complicated by anomalous within-NH and interhemispheric mixing. Resumption of atmospheric behaviour more consistent with emission estimates coincides with improved national emissions accounting at COP21. There is relevance to top-down air-surface flux estimates, for example, recent conflicting transport model estimates of Chinese emission trends or El Niño induced emissions.

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 score0.058
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.042
GPT teacher head0.317
Teacher spread0.275 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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