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Record W4210900747 · doi:10.29169/1927-5129.2022.18.03

The Sun Versus CO2 as the Cause of Climate Change Projected to 2050

2022· article· en· W4210900747 on OpenAlexaffvenue
H. Douglas Lightfoot, Gerald Ratzer

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSolar and Space Plasma Dynamics
Canadian institutionsMcGill University
Fundersnot available
KeywordsEnvironmental scienceClimate changeGlobal warmingWater vaporAtmospheric sciencesClimatologyMeteorologyNatural resource economicsGeographyGeologyEconomicsOceanography

Abstract

fetched live from OpenAlex

The current controversy over the cause of increasing global temperatures since the middle of the 20th century comes from the IPCC First Assessment Report issued in 1990. The report states rising carbon dioxide (CO2) warms the air, thereby holding more of the significant warming gas, water vapor. This additional water vapor feeds back to amplify the warming by CO2. The IPCC has continually promoted this concept in its reports since 1990. Up-to-date science proves the IPCC concept is faulty. Scientists discovered that when the Sun's energy output changes, it impacts the Earth's temperature, and it does this cyclically. Current, reliable evidence shows the Earth has just come through a warm period. It is now in the early stages of cooling that might be similar to the Dalton Minimum and last for three or four decades. Average temperatures can drop by up to 1.5oC and increase the rate of crop failures that have already started. It won't be easy to maintain the benefits of the recent warm phase of the Sun during the upcoming solar minimum.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.030
GPT teacher head0.285
Teacher spread0.255 · 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 designSimulation or modeling
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

Citations3
Published2022
Admission routes2
Has abstractyes

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