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Record W1884808726

Determination of the atmospheric optical depth due to the El Chichon stratospheric aerosol cloud in the polluted atmosphere of Mexico City

2009· article· en· W1884808726 on OpenAlexaboutno aff
Ignacio Galindo, K. Ya. Kondratyev, Gerardo Zenteno

Bibliographic record

VenueAtmósfera · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric aerosols and clouds
Canadian institutionsnot available
Fundersnot available
KeywordsAerosolVolcanoEnvironmental scienceAtmosphere (unit)Atmospheric sciencesVolcanic ashMexico cityVulcanian eruptionMeteorologyClimatologyGeologyGeography
DOInot available

Abstract

fetched live from OpenAlex

Direct solar radiation measurements were used to determine the aerosol optical depth (AOD) increase associated with the presence of aerosol and large particles (ash) originating from the 28 March to 4 April 1982 El Chichon eruptions (17.5oN, 93.3oW; Mexico) on Mexico City's polluted atmospheric aerosol layer. The results are compared with those obtained at Vancouver, British Columbia, revealing that a first AOD increase occurred in both locations during May, June, and July 1982. However, the Mexico City AOD decay is more extended, not reaching normal climatological values until February 1983. Meanwhile, Vancouver's AOD reached minimum values in September 1982, which subsequently increased over a period from October 1982 to September 1983. This secondary maximum was recorded in Mexico City from March to August 1983. Results suggest that the first AOD increases in May, June and July 1982, both at Vancouver and Mexico City, are due chiefly to short life-time volcanic ash particles being located near the surface. However, the second AOD increases, associated with anomalously colored twilights, corresponds to stratospheric volcanic aerosols.

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 score0.114
Threshold uncertainty score0.226

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
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 head0.234
Teacher spread0.225 · 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

Citations1
Published2009
Admission routes1
Has abstractyes

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