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Record W4294094068 · doi:10.14738/assrj.98.12935

Collapse of Earth’s Biosphere: A Case of Planetary Treason

2022· article· en· W4294094068 on OpenAlexaboutno aff
J. Marvin Herndon, Mark Whiteside

Bibliographic record

VenueAdvances in Social Sciences Research Journal · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Geoengineering
Canadian institutionsnot available
Fundersnot available
KeywordsOzone layerStratosphereOzone depletionHydrosphereEnvironmental scienceAstrobiologyAtmospheric sciencesTroposphereBiosphereClimatologyEarth scienceGeologyPhysicsAstronomy

Abstract

fetched live from OpenAlex

Earth’s life support systems are breaking down, including the stratospheric ozone layer, which protects all higher life on the planet from deadly ultraviolet radiation. This breakdown is a direct result of human activities including the large-scale manipulation of processes that affect Earth’s climate, otherwise known as geoengineering. We present further evidence that coal fly ash, utilized in tropospheric aerosol geoengineering, is the primary cause of stratospheric ozone depletion, not chlorofluorocarbons, as “decreed” by the Montreal Protocol. The misdiagnosis was a potentially fatal mistake by mankind. Coal fly ash particles, uplifted to the stratosphere, are collected and trapped by polar stratospheric clouds. In springtime, as these clouds begin to melt/evaporate, multiple coal fly ash compounds and elements are released to react with and consume stratospheric ozone. Contrary to the prevailing narrative, the stratospheric ozone layer has already been badly damaged and now increasingly deadly ultraviolet radiation, UV-B and UV-C, penetrates to Earth’s surface. Our time is short to permanently end all geoengineering activities, and to reduce and/or eliminate all sources of aerosolized coal fly ash, including first and foremost the jet-sprayed emplacements into the troposphere that are systematically breaking down Earth’s support systems and poisoning life on this planet.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.426
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.069
GPT teacher head0.394
Teacher spread0.325 · 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.

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
Published2022
Admission routes1
Has abstractyes

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