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Record W2155875073 · doi:10.1080/10889860290777477

Phytotoxicity Assay to Assess Plant Species for Phytoremediation of Petroleum-Contaminated Soil

2002· article· en· W2155875073 on OpenAlexafffundabout
Jennifer L. Kirk, John N. Klirnomos, Hung Lee, J. T. Trevors

Bibliographic record

VenueBioremediation Journal · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial bioremediation and biosurfactants
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhytoremediationLolium perennePhytotoxicityGerminationBioassayAgronomyBiologySoil contaminationMedicago sativaEnvironmental sciencePerennial plantBotanyContaminationEcology

Abstract

fetched live from OpenAlex

A phytotoxicity bioassay was used to select plant species for phytoremediation that were able to germinate and grow in petroleum-contaminated soil from an industrial site in Canada. Perennial ryegrass (Lolium perenne var. “Affinity”) and alfalfa (Medicago sativa L.) were more successful at germination and root growth than were little bluestem (Schizachyrum scoparium) and crown vetch (Coronilla varia). The phytotoxicity assay provides a rapid, efficient mechanism of prescreening potential plant species and eliminating those not able to germinate and establish in soil conditions present at the contaminated site. This bioassay can potentially reduce the number of pot or greenhouse degradation studies that need to be conducted before plant species can be chosen for petroleum phytoremediation.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.189
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0030.000

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 head0.046
GPT teacher head0.233
Teacher spread0.187 · 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 teacher head, not a consensus.

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

Citations66
Published2002
Admission routes3
Has abstractyes

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