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Record W2610165679 · doi:10.1139/cjce-2016-0500

Suitability of hazard rating systems for air contamination from municipal solid waste dumps and improvements to enhance performance

2017· article· en· W2610165679 on OpenAlex
Amit Kumar, Manoj Datta, Arvind K. Nema, Raj Singh

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicRecycled Aggregate Concrete Performance
Canadian institutionsnot available
FundersScience and Engineering Research BoardDepartment of Science and Technology, Ministry of Science and Technology, India
KeywordsMunicipal solid wasteHazardous wasteEnvironmental remediationContaminationRating systemEnvironmental scienceWaste managementHazardHazard analysisEnvironmental hazardEnvironmental engineeringEngineeringReliability engineering

Abstract

fetched live from OpenAlex

Close vicinity of uncontrolled municipal waste sites (or ‘waste dumps’) to well-populated communities makes the air contamination a prominent hazard from the waste dumps. The hazard rating systems, considered useful in prioritizing these sites for remediation, are investigated for their suitability to assess air contamination of municipal solid waste (MSW) dumps. Out of the eight systems employed in the study, six rating systems respond well to changes in site conditions when applied to hazardous waste sites. However for MSW sites, all eight rating systems give scores in a narrow range and do not perform well. One system is selected for improvement by modifying the indicators for waste quantity and rainfall and, introducing the indicators for waste composition and fresh waste quantity using expert judgment. The modified system performs well for MSW dumps, produces air contamination hazard ratings in a wider range, and responds to higher number of scenarios in sensitivity analysis, thus making it an appropriate tool for site prioritization for remediation.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.222
Teacher spread0.213 · 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