MétaCan
Menu
Back to cohort
Record W4367154861 · doi:10.36487/acg_repo/2355_64

Critical timelines and pathways: addressing environmental, social, governance and permitting

2023· article· en· W4367154861 on OpenAlexaff
Jack Kellner, Andrew Hall, Fallon Tanentzap

Bibliographic record

VenuePaste/˜Pœaste · 2023
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsBanff CentreGeomechanica (Canada)University of Alberta
Fundersnot available
KeywordsTimelineCorporate governanceComputer scienceProcess managementBusinessGeography

Abstract

fetched live from OpenAlex

The need for projects to focus on permitting and environmental, social and governance (ESG) considerations is increasingly prioritised over the technical and economic aspects of backfill and tailings solutions. This includes not only environmental permitting, but also takes into account public perception and responses to a project, as well as local community engagement and support. To optimise the success of a project, it is essential to incorporate and understand both the mining companies’ ESG frameworks and the local and governmental permitting requirements from the beginning. There is a need to pull these more advanced backfill and tailings designs earlier into the process to satisfy permitting requirements rather than the usual execution schedule. Permitting timelines may also lead to temporary backfill solutions such as cemented rockfill until paste backfill can be permitted and implemented. Comparing surface versus underground permitting requirements can lead to a more strategic approach by evaluating alternative solutions for infrastructure placement. For example, some facilities can be located underground if surface is perceived to be contentious. This can also lead to an approach where facility placement that might be better suited underground, but a more conservative approach is to start on surface and move underground as the project progresses. Given the focus on ESG and permitting and the timelines involved, it is more important than ever to provide a narrative which conveys a responsible integrated tailings solution for mining projects, both for permitting and to ensure public support.

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.888
Threshold uncertainty score0.755

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.299
GPT teacher head0.476
Teacher spread0.177 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venuePaste/˜PœasteSame topicEvaluation and Performance AssessmentFrench-language works237,207