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Vitamin B <sub>12</sub> and Reduced Titanium for Remediation of Residual Chlorinated Solvents: Field Experiment

2001· article· en· W2079900568 on OpenAlexaff
Dominique Sorel, Suzanne Lesage, Susan Brown, Kelly Millar

Bibliographic record

VenueGroundwater Monitoring & Remediation · 2001
Typearticle
Languageen
FieldEngineering
TopicEnvironmental remediation with nanomaterials
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsEnvironmental remediationChemistryDegradation (telecommunications)BiodegradationRedoxTitaniumEnvironmental chemistryContaminationChromatographyNuclear chemistryInorganic chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract A first pilot‐scale field experiment using vitamin B 12 and reduced titanium was conducted in an in situ vertical circulation column at CFB Borden. The objective of the experiment was to test the applicability of the technology for restoring aquifer source zones contaminated by chlorinated solvents—tetrachloroethene (PCE) and 1,1,1‐trichloroethane (1,1,1‐TCA)—in a mixture of dense nonaqueous phase liquids (DNAPLs). Vitamin B 12 promotes the reductive dechlorination of chlorinated organics. A highly reducing and slightly alkaline environment must be maintained (Eh < ‐ 480 mV and 7 < pH < 9) to maximize the rate of degradation. In this field test, PCE and 1,1,1‐TCA degraded to a limited extent under experimental conditions, with 1,1,1‐TCA degrading more readily. Indigenous bacteria were found to metabolize citrate, which caused titanium to precipitate, limiting degradation. The addition of glucose at the end of a second field season effectively limited citrate degradation and helped recover the optimal redox potential by keeping reduced titanium in solution. A laboratory column was used to confirm field results. The column also produced a significant biomass, which provided an additional source of organic carbon onto which the solvents sorbed.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.232
Teacher spread0.217 · 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 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

Citations16
Published2001
Admission routes1
Has abstractyes

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