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Record W2304151518 · doi:10.1680/jenge.15.00063

New Turcot complex: the challenge of contamination management

2016· article· en· W2304151518 on OpenAlexaff
Nicolas Sbarrato, Claude Marcotte

Bibliographic record

VenueEnvironmental Geotechnics · 2016
Typearticle
Languageen
FieldEngineering
TopicInfrastructure Maintenance and Monitoring
Canadian institutionsEnGlobe (Canada)Nordion (Canada)
Fundersnot available
KeywordsContaminationEnvironmental remediationHazardous wasteEnvironmental scienceEngineeringWaste managementEnvironmental engineering

Abstract

fetched live from OpenAlex

At the heart of the Turcot reconstruction project, the Turcot rail yard, which has hosted railway activities for more than a century, has a long contamination heritage, mainly due to oil spills and backfilling episodes when fill materials were put over lacustrine deposits. The remediation of the site relies on a risk analysis allowing contaminated soils and non-hazardous materials to be maintained in place. Over 4·3 Mm3 of fill materials, including burnt coal residue, parts of which are contaminated, will need to be excavated and managed for the construction of a new complex in accordance with the objectives of a risk analysis and the requirements of regulatory agencies. The data correlation analysis between soil composition and levels of contamination, the development of databases and algorithms allowing extrapolation of chemical data to uncharacterised materials and the volume calculation all helped add environmental value to the project from its design to its construction including its regulatory framework.

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)0.002
metaresearch head score (Gemma)0.004
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: none
Teacher disagreement score0.047
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.003
Scholarly communication0.0090.004
Open science0.0030.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.002

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 head0.005
GPT teacher head0.173
Teacher spread0.168 · 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
Published2016
Admission routes1
Has abstractyes

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