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Record W7023359060

Oil & gas wellsite reclamation criteria in Alberta : bioremediation of invert drilling waste

2009· article· en· W7023359060 on OpenAlexaffabout

Bibliographic record

VenuecIRcle (University of British Columbia) · 2009
Typearticle
Languageen
FieldMaterials Science
TopicMicrostructure and mechanical properties
Canadian institutionsNova Chemicals (Canada)
Fundersnot available
KeywordsArticular cartilage damageDiafiltrationProteogenomicsTSG101Fusible alloyGestational period
DOInot available

Abstract

fetched live from OpenAlex

The fundamental principle of wellsite reclamation criteria is that reclaimed site conditions are to be assessed by comparing them to documented pre-disturbance conditions, or adjacent lands. The differences must not interfere with normal land use and must support comparable self-sustainable growth.\nProper waste management and disposal methods which permit drilling operations to take place with temporary effects on the land, while also reducing the cost and time required to obtain final reclamation, are \nintegral steps in successful site reclamation. The goal of all disposal options is to protect the environment and \nreturn the disposal site and any affected areas to equivalent land capability.\nLandfarming is a drilling waste disposal option for heavy invert mud system. By applying the drilling wastes over a selected plot of land and keeping the waste application within loading limits set by ERCB, landfarming is a productive efficient method of reclaiming contaminated sites.\nLandfarming may take place in either the topsoil or the subsoil, although the topsoil has been shown to provide a more favorable environment for microbial biodegradation of hydrocarbons in invert drilling muds. Due to the soil texture, nutrient availability and increased aeration, landfarming in the topsoil may lead to a more efficient and faster degradation rate of the drilling waste.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.887
Threshold uncertainty score0.924

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.010
GPT teacher head0.185
Teacher spread0.175 · 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 designBench or experimental
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
Published2009
Admission routes2
Has abstractyes

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