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Record W7132882085

Enhanced dissolution of a tetrachloroethylene DNAPL in a two dimensional model aquifer

2003· dissertation· W7132882085 on OpenAlexfundno aff
David John Seepersad

Bibliographic record

VenueTSpace · 2003
Typedissertation
Language
FieldEnvironmental Science
TopicMicrobial bioremediation and biosurfactants
Canadian institutionsnot available
FundersEnvironmental Security Technology Certification ProgramGovernment of OntarioUniversity of TorontoMcMaster University
KeywordsBioaugmentationBiostimulationAquiferTetrachloroethyleneGroundwaterBioremediationDissolutionBiodegradation
DOInot available

Abstract

fetched live from OpenAlex

The objectives of this project are to determine the potential for anaerobic microbial cultures to biodegrade chlorinated ethenes present as dense, non-aqueous phase liquid (DNAPL) and to determine the potential for biodegradation to enhance mass transfer rates from the DNAPL into the aqueous phase. The effect of enhanced bioremediation on DNAPL was evaluated using two-dimensional model aquifers containing a tetrachloroethene (PCE) DNAPL. This study involved the construction and operation of a two dimensional model aquifer using a PCE DNAPL. Duplicate model aquifers were constructed, one serving as a control for the other. The model aquifers were packed with soil collected from Dover Air Force Base, DE. The study consisted of four phases: setup, groundwater flush, biostimulation and bioaugmentation with KB-1, an enriched dechlorinating culture. During biostimulation, no observable increase in mass flux was observed, but bioaugmentation doubled the rate of dissolution compared to the control model aquifer.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

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 head0.015
GPT teacher head0.307
Teacher spread0.292 · 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 designSimulation or modeling
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
Published2003
Admission routes1
Has abstractyes

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