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Record W7147701174 · doi:10.65615/hj2b9539

Le contexte nouveau du fer canadien

2021· article· W7147701174 on OpenAlexaffabout
Théophore Gaëtan Badjo

Bibliographic record

VenueEra Novum revue académique interdisciplinaire d enjeux sociaux et environnementaux · 2021
Typearticle
Language
FieldEngineering
TopicMining and Resource Management
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsChampionSustainabilityGovernment (linguistics)Corporate governanceTailingsSustainable developmentBalance (ability)

Abstract

fetched live from OpenAlex

Today, public welfare and respect for the balance of ecosystems are among the objectives of the profession of urban planners. These interesting development issues are the subject of this article, which focuses on the environmental and social management of iron ore operations at lake Bloom by Minerai de Fer Québec, the subsidiary of Champion Iron Limited. Ananalysis of the project to increase the storage capacity of residual materials from this operation was conducted to determine whether the company is acting in favour of sustainable development objectives. The notions of metal pollution, water acidification and the disappearance of fauna and flora species were addressed. The analysis of the social and governance issues of the mining project took into account three issues: business conduct, working conditions on the site and the well-being of the affected communities. Finally, lessons learned and important recommendations for tailings management were presented

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)0.003
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 score0.185
Threshold uncertainty score0.438

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0290.022
Scholarly communication0.0090.003
Open science0.0020.005
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0250.001

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 head0.017
GPT teacher head0.251
Teacher spread0.234 · 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
Published2021
Admission routes2
Has abstractyes

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