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Record W2185491817

Seismic Characterization of CO2 in Coals

2008· article· en· W2185491817 on OpenAlexaffabout
Jason McCrank, Don C. Lawton

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicCoal Properties and Utilization
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCoalbed methaneGeologyPetroleum engineeringPermeability (electromagnetism)CoalSeismic surveyCoal miningCarbon sequestrationEnvironmental scienceMining engineeringCarbon dioxideSeismologyWaste managementEngineering
DOInot available

Abstract

fetched live from OpenAlex

Summary A high resolution 3D surface seismic survey was aquired by the University of Calgary at a pilot project site in Alberta for testing enhanced coalbed methane (CBM) production using CO2. The multi-well pilot project, in the Pembina Field of west-central Alberta, intends to test the Ardley coals for CO2 injection, enhanced CBM production, and CO2 sequestration. The seismic survey captured the condition of the reservoir after formation permeability tests, which involved injecting a small volume of CO2 into the target Mynheer coal seam, but before commencement of continuous CO2 injection. Anomalies are seen in the seismic data which are possibly attributable to changes in the physical properties of the coal due to CO2 adsorption.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.182
Teacher spread0.166 · 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

Citations0
Published2008
Admission routes2
Has abstractyes

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