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Record W2770112543 · doi:10.14288/1.0314303

Assessing reclamation ready tailings materials using outdoor terrestrial mesocosms

2017· article· en· W2770112543 on OpenAlexaboutno aff
Christina C. Small, Jay Woosaree, M. Anne Naeth

Bibliographic record

VenuecIRcle (University of British Columbia) · 2017
Typearticle
Languageen
FieldEngineering
TopicTailings Management and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsTailingsLand reclamationEnvironmental scienceArchaeologyGeographyMetallurgy

Abstract

fetched live from OpenAlex

Current challenges in oil sands mine closure include the integration of tailings into reclaimed landscapes to ensure that materials are geotechnically stable; have acceptable soil; water and run-off quality; permit soil development consistent with regional soils; and, have ecological aspects of form and function consistent with the boreal forest. Infrastructure available in Alberta to facilitate feasible, controlled and replicated testing of tailings materials under realistic climate, environmental and exposure conditions is lacking. The Terrestrial Mesocosm Facility was designed to provide a relevant venue for testing engineered ecosystems, such as reconstructed soils. Mesocosms can include sufficient biotic and abiotic components to confer stability under replicated and controlled conditions; experiments can be conducted on time frames ranging from months to years. The facility represents an integrative scientific approach for investigating ecological and environmental systems by utilizing both laboratory and field data to develop complex assessments of indirect and synergistic ecosystem responses. Simultaneous testing of different scenarios can be completed as a feasible first step in identifying reclamation strategies to implement on-site; associated long-term monitoring may provide valuable information necessary for determining upland vegetation establishment success. This paper introduces a tool for testing tailings for reclamation planning and environmental effects assessment.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.974
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 studies0.0010.000
Scholarly communication0.0010.002
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 head0.033
GPT teacher head0.216
Teacher spread0.183 · 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.

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

Citations2
Published2017
Admission routes1
Has abstractyes

Explore more

Same venuecIRcle (University of British Columbia)Same topicTailings Management and PropertiesFrench-language works237,207