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Record W2000498955 · doi:10.1134/s0097807809060116

Climatic trends in the middle and high latitudes of the Northern Hemisphere

2009· article· en· W2000498955 on OpenAlexaboutno aff
Г. Н. Панин, I. V. Solomonova, T. Yu. Vyruchalkina

Bibliographic record

VenueWater Resources · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsnot available
Fundersnot available
KeywordsNorthern HemisphereClimate changeClimatologyLatitudeGreenhouse gasSouthern HemisphereClimate modelEnvironmental scienceZoningGeographyGeologyOceanography

Abstract

fetched live from OpenAlex

Air temperature variations are studied in the territory of the middle and high latitudes of the Northern Hemisphere. Estimates of the intraregional homogeneity of current climate changes were used to carry out zoning by several criteria for the XX and early XXI centuries. Six zones with typical climate change were identified: the Pacific, Canadian, Atlantic, European, Siberian, and Far Eastern. A new approach is proposed to the description of possible regional and global climate changes in the Northern Hemisphere basing on a combination of “greenhouse” and “rotational” effects. It is shown that the data on variations in the angular velocity of the Earth’s rotation can be used as a universal indicator of climate changes on the planet. The proposed approach made it possible to account for not only the growth in temperature caused by greenhouse gas emission, but also climate changes (in particular, the cooling of the 1940s–1970s). A concept is developed, allowing a new scenario of possible climate changes in the XXI century to be proposed.

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 score0.018
Threshold uncertainty score0.036

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 head0.019
GPT teacher head0.209
Teacher spread0.190 · 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

Citations14
Published2009
Admission routes1
Has abstractyes

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