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Record W7029923560

Measurement campaign on the landfill site of Mont-saint-Guibert. Setup of an annoyance assessment method.

2002· report· en· W7029923560 on OpenAlexaff

Bibliographic record

VenueORBi (University of Liège) · 2002
Typereport
Languageen
Field
Topic
Canadian institutionsGDG Environnement
Fundersnot available
KeywordsAnnoyanceChristian ministryAtmospheric dispersion modelingSniffingFrame (networking)Dispersion (optics)Field (mathematics)Atmospheric emissions
DOInot available

Abstract

fetched live from OpenAlex

The study is made in the frame of a follow-up monitoring of all landfill sites in Wallonia, initiated by the Ministry of Environment and managed by ISSeP. The research group applied a field inspection technique based on the perception of a panel of experts sniffing the air around the region of interest and trying to delineate the odour plume. In a second step, the recorded meteorological data are entered into an atmospheric dispersion model and the odour emission rate of the facility is adjusted until the predicted odour impact zone fits about exactly the one which is measured in the field. The present report is the first one of a long series of measurement campaigns. It presents in details the used methodology and the results of the study.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.086
GPT teacher head0.298
Teacher spread0.212 · 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

Citations0
Published2002
Admission routes1
Has abstractyes

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