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Record W2007996678 · doi:10.1002/rem.20233

Evaluation of algal phytoremediation of light extractable petroleum hydrocarbons in subarctic climates

2009· article· en· W2007996678 on OpenAlex
Nicole R. Jacques, Dena W. McMartin

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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueRemediation Journal · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial bioremediation and biosurfactants
Canadian institutionsUniversity of Regina
FundersU.S. Food and Drug AdministrationGovernment of CanadaU.S. Environmental Protection Agency
KeywordsSubarctic climateEnvironmental remediationAlgaePetroleumEnvironmental chemistryEnvironmental sciencePhytoremediationHydrocarbonContaminationChemistryGeologyEcologyOceanographyBiologyHeavy metals

Abstract

fetched live from OpenAlex

Abstract The presence of an organic mat in a hydrocarbon‐impacted creek in Whitehorse, Yukon Territory, Canada was examined for contributions to in situ remediation of petroleum‐contaminated water. This article investigates the role of algae, found in the organic mat, in the remediation of light extractable petroleum hydrocarbons (LEPHs) at the site and in the laboratory. During the study, LEPH concentrations were reduced by 16.8 percent in the presence of algae alone (algal solution) and 30.4 percent in the combined organic mat solution containing microbial consortia. The study results indicate that algal species at the site did not directly phytoremediate hydrocarbons. Rather, they were part of the total biological degradation taking place. © 2009 Wiley Periodicals, Inc.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.622
Threshold uncertainty score0.933

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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)0.0010.000

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 head0.015
GPT teacher head0.254
Teacher spread0.239 · 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