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Record W4409202774 · doi:10.1080/17538947.2025.2487058

Evaluation and prediction of the effects of planetary orbital variations to earth’s temperature changes

2025· article· en· W4409202774 on OpenAlexaff
Mengmeng Cao, Kebiao Mao, Sayed M. Bateni, Jing M. Chen, Essam Heggy, Jong‐Seong Kug, Xinyi Shen

Bibliographic record

VenueInternational Journal of Digital Earth · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsUniversity of Toronto
FundersNational Key Research and Development Program of ChinaNatural Science Foundation of Henan Province
KeywordsEarth (classical element)AstrobiologyGeographyGeologyGeophysicsPhysicsAstronomy

Abstract

fetched live from OpenAlex

The influence of planetary orbital changes on Earth’s temperature has been poorly quantified and subject to speculation. Here, we delineated the effects of greenhouse gases and planetary orbital changes on Earth’s temperature and forecasted the latter. Our results indicate that Earth’s revolution around the Sun and its rotation explain ∼75.36% and 15.91% of Earth’s temperature variations in one year, while the Moon’s revolution around the Earth and other planet motions account for 8.26% and 0.26%, respectively. Orbital forcings contributed ∼11.5% global warming since 1837 and will continue to warm the Earth by ∼0.13 °C from 2020 to 2027. However, orbital forcings may contribute to ∼0.25 °C cooling of Earth from 2027 to 2050, but this effect remains insufficient to offset the warming caused by CO₂

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.516
Threshold uncertainty score0.143

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.009
GPT teacher head0.238
Teacher spread0.229 · 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 teacher head, 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
Published2025
Admission routes1
Has abstractyes

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