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Record W4394813591 · doi:10.29169/1927-5129.2024.20.05

Reliable Physics Demand Revision of the IPCC Global Warming Potentials

2024· article· en· W4394813591 on OpenAlexaffvenue
H. Douglas Lightfoot, Gerald Ratzer

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsMcGill University
Fundersnot available
KeywordsGlobal warmingNitrous oxideGlobal-warming potentialEnvironmental scienceTable (database)MethaneAtmosphere (unit)Climate changeAtmospheric sciencesGreenhouse gasClimatologyMeteorologyChemistryPhysicsComputer scienceEcologyDatabase

Abstract

fetched live from OpenAlex

The Global Warming Potentials (GWP) of the Intergovernmental Panel on Climate Change (IPCC) in Table 2.14 of the Fourth Assessment Report (AR4) show the increase in warming by methane (CH4) and nitrous oxide (N2O) is 21 and 310 times respectively that of CO2. There has been wide acceptance of these values since publishing in 2007. Nevertheless, they are inaccurate. This study uses accurate methods to calculate the impacts of CO2, CH4, and N2O on the warming of the atmosphere. For example, this quantitative analysis from reliable physics shows the contribution of CO2 to warming at Amsterdam is 0.0083oC out of a difference of 26oC. The warming effect of CH4 on the Earth’s atmosphere is 0.408% of that of CO2, and the warming by N2O is 0.085% of that of CO2. Thus, the warming effects of CO2, CH4, and N2O are too small to measure. The invalidity of the methane and nitrous oxide values indicates the GWPs of the remaining approximately sixty chemicals in the Table 2.14 list are also invalid. A recommendation is that the IPCC consider revising or retracting the GWP values in Table 2.14.

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)0.029
metaresearch head score (Gemma)0.108
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.029
Threshold uncertainty score0.154

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.108
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.003
Science and technology studies0.0010.002
Scholarly communication0.0050.010
Open science0.0030.003
Research integrity0.0030.009
Insufficient payload (model declined to judge)0.0070.004

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 head0.008
GPT teacher head0.228
Teacher spread0.219 · 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 designTheoretical or conceptual
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

Citations4
Published2024
Admission routes2
Has abstractyes

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