MétaCan
Menu
Back to cohort
Record W2005866035 · doi:10.1021/es030340v

Trichloroethylene Degradation in a Coupled Anaerobic/Aerobic Reactor Oxygenated Using Hydrogen Peroxide

2003· article· en· W2005866035 on OpenAlexaff
B. Tartakovsky, Manju Manuel

Bibliographic record

VenueEnvironmental Science & Technology · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsBiotechnology Research Institute
Fundersnot available
KeywordsTrichloroethyleneChemistryHydrogen peroxideBiofilmAnaerobic exerciseBiodegradationDegradation (telecommunications)Environmental chemistryMicroorganismBacteriaOrganic chemistryBiology

Abstract

fetched live from OpenAlex

In this work, trichloroethylene (TCE) degradation under combined anaerobic-aerobic conditions was studied in an ethanol-fed biofilm reactor oxygenated using hydrogen peroxide. The reactor was inoculated with a biomass originating from an anaerobic digestor. Granulated peat was added to the reactor as a substratum for biofilm development. Extensive characterization of reactor populations using activity tests and PCR analysis revealed the development of a mutualistic consortium, particularly methanotrophic and methanogenic microorganisms. This consortium was shown to degrade TCE by a combination of reductive and oxidative pathways. A near complete degradation of TCE at a load of 18 mg L(R)(-1) day(-1) was evidenced by a stoichiometric release of inorganic chloride.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
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 head0.011
GPT teacher head0.216
Teacher spread0.205 · 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

Citations23
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueEnvironmental Science & TechnologySame topicWastewater Treatment and Nitrogen RemovalFrench-language works237,207