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Record W2945594132 · doi:10.36646/mjlr.19.4.reducing

Reducing Acid Rain in Eastern North America: The Scientific Basis for an Acid Rain Control Policy

2025· article· en· W2945594132 on OpenAlexaboutno aff
Michael Oppenheimer

Bibliographic record

VenueUniversity of Michigan Journal of Law Reform · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsnot available
Fundersnot available
KeywordsAcid rainControl (management)Natural resource economicsEnvironmental scienceEcologyEconomicsBiology

Abstract

fetched live from OpenAlex

This Article presents the scientific basis for an effective acid rain control policy. Part I suggests that if a choice must be made, regulation should focus primarily on sulfur dioxide emissions rather than nitrogen oxide emissions because sulfur deposition is the major cause of watershed acidification. Part II explains the need for at least a fifty percent reduction in sulfur dioxide emissions to meet a "safe" deposition level. Part III specifies the geographical allocation of sulfur emission reductions necessary to attain target deposition levels in the northeastern United States and southeastern Canada. The Article concludes by demonstrating the need for swift adoption and implementation of an effective acid deposition control strategy in light of large future risks of accumulating irreversible damage.

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)0.006
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.059
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.013
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0020.000

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 head0.211
Teacher spread0.202 · 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 designNot applicable
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
Published2025
Admission routes1
Has abstractyes

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Same venueUniversity of Michigan Journal of Law ReformSame topicSmart Materials for ConstructionFrench-language works237,207