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Record W2315018392 · doi:10.3130/aija.78.1077

LEGAL FRAMEWORK AND ESTIMATED STOCK MEASUREMENT ON BROWNFIELD AS CONTAMINATED LAND IN ENGLAND AND JAPAN

2013· article· en· W2315018392 on OpenAlexaff
A Takahashi, Hirokazu Abe, Noriko Otsuka, Tomoko Miyagawa

Bibliographic record

VenueJournal of Architecture and Planning (Transactions of AIJ) · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental Justice and Health Disparities
Canadian institutionsLearning Partnership
Fundersnot available
KeywordsBrownfieldContaminated landContaminationEnvironmental scienceStock (firearms)GeographyEnvironmental planningEnvironmental protectionEngineeringArchaeologyCivil engineeringRedevelopmentEnvironmental remediationBiologyEcology

Abstract

fetched live from OpenAlex

This paper aims to identify current situation of soil contamination countermeasures for England and Japan.It examines the legal framework and estimated stock measurement on contaminated land between the two countries.The primary findings are as follows: 1) The main differences in the Acts for soil contamination between the two countries are found in triggers for inspection, initiatives and ways of handling the whole process of remediation; 2) The number of estimated contaminated sites in the both countries is approximately 330,000.And the rate of site investigations is approximately three times in England than that in Japan; 3) Regarding the soil contamination counter measure, Environmental Act (EPA1990) and planning system (Planning 1990) are closely and jointly well operated in England; and 4) In England the local authority needs to take a strategic approach to the inspection of sites within their district boundary under EPA1990 and each contaminated site is handled by a risk based approach (CLEA) on the comprehensive evaluation of pollutant linkage and land use.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.369
Threshold uncertainty score0.733

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.298
Teacher spread0.272 · 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
Published2013
Admission routes1
Has abstractyes

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