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Record W2345143933 · doi:10.12723/mjs.1.11

ACID RAIN-AN INVISIBLE THREAT

2002· article· en· W2345143933 on OpenAlexaboutno aff
Prashant Anthony

Bibliographic record

VenueMapana Journal of Sciences · 2002
Typearticle
Languageen
FieldPhysics and Astronomy
TopicScientific Research and Discoveries
Canadian institutionsnot available
Fundersnot available
KeywordsAlkalinityAcid rainPrecipitationEnvironmental chemistryAtmosphere (unit)Rain and snow mixedSnowNitric acidNitrogenChemistryEnvironmental scienceInorganic chemistryMeteorologyGeography

Abstract

fetched live from OpenAlex

Acid Rain is defined as precipitation (rain) that has a pH lower than 5.6, which is the pH expected in distilled water exposed to the atmosphere. (pH is a measure ot the acidity or alkalinity of a water sample.) The pH Of precipitation undoubtedly is affected by a variety of natural sources of acidic and alkaline materials (e.g. volcanic gases, gases from decompoSng Organic matter and soil dust). However it has recently become apparent that rain and snow in certain regions of the earth are consistently more acidic than expected. The European Atmosphere Chemistry Net Work first recognized that the pH of precipitation was declining in Scandinavia during the late 1960's. Current data indicates that the mean annual pH in this region was 5.0 - 5.5 in the late 1950's which declined to 4.2 • 4.4 in the mid 1970's. In Eastern North America precipitation is now more acidic than in Scandinavia. The median pH for 1978 • 1979 ranged from 4.0 to 4.4 in North Eastern U.S. and South Eastem Canada. Although there is disagreement over the Source and nature Of acidic precipitation , the most widely accepted view is that the increased acidity is a result of the presence Of increased quantities Of sulphuric and nitric acids. These acids are believed to result from oxidation Of sulphur and nitrogen oxide gases. Oxides of sulphur and nitrogen are produced from combustion of fossil fuels, metal smelting and various industrial processes.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.409
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.065
GPT teacher head0.314
Teacher spread0.248 · 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 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

Citations0
Published2002
Admission routes1
Has abstractyes

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