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Record W1995545556 · doi:10.1080/15567036.2010.492380

A Laboratory Study for Assessing Microbial Enhanced Oil Recovery

2013· article· en· W1995545556 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnergy Sources Part A Recovery Utilization and Environmental Effects · 2013
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsConcordia University
Fundersnot available
KeywordsMicrobial enhanced oil recoveryResidual oilMicroorganismEnhanced oil recoveryEnvironmental sciencePetroleum engineeringRecovery ratePulp and paper industryChemistryChromatographyGeologyBacteriaEngineering

Abstract

fetched live from OpenAlex

Microbial enhanced oil recovery utilizes microorganisms and their metabolic products to improve the oil recovery. A pilot scale study was conducted to investigate the effectiveness of two microorganisms (D-2 and M-1), presenting as an individual and a mixture, by recovering residual oil from a sandstone core oil reservoir at Shengli Oil Reservoir, China. Five microbial flooding tests were conducted sequentially by injecting microbial cultures into the experimental reservoir. The results showed that a polymer surfactant produced by D-2, M-1, and their mixture, enhanced oil recovery by 5.4, 5.6, and 7.9%, respectively, which are within the reported ranges of increased tertiary oil recovery.

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.

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 categoriesMeta-epidemiology (narrow)
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 score0.517
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 studies0.0000.000
Scholarly communication0.0000.001
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 head0.006
GPT teacher head0.204
Teacher spread0.197 · 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