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Record W2074670408 · doi:10.1080/10934521003772436

Phytotoxicity and naphthenic acid dissipation from oil sands fine tailings treatments planted with the emergent macrophyte<i>Phragmites australis</i>

2010· article· en· W2074670408 on OpenAlexaff
Sarah A. Armstrong, John V. Headley, Kerry M. Peru, Randy J. Mikula, James J. Germida

Bibliographic record

VenueJournal of Environmental Science and Health Part A · 2010
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsUniversity of SaskatchewanNatural Resources CanadaEnvironment and Climate Change Canada
Fundersnot available
KeywordsPhragmitesTailingsOil sandsEnvironmental scienceLand reclamationSurface runoffNaphthenic acidPhytotoxicityPhytoremediationSoil waterAgronomyChemistryWetlandEcologyAsphaltSoil scienceBiology

Abstract

fetched live from OpenAlex

During reclamation the water associated with the runoff or groundwater flushing from dry stackable tailings technologies may become available to the reclaimed environment within an oil sands lease. Here we evaluate the performance of the emergent macrophyte, common reed (Phragmites australis), grown in chemically amended mature fine tailings (MFT) and simulated runoff/seepage water from different MFT drying treatments. The present study also investigated the phytotoxicity of the concentration of oil sands naphthenic acids (NAs) in different MFT drying chemical treatments, in both planted and unplanted systems. We demonstrate that although growth was reduced, the emergent macrophyte common reed was capable of growing in diluted unamended MFT runoff, as well as in diluted runoff from MFT amended with either 0.25% lime and gypsum or 0.5% gypsum. Common reed can thus assist in the dewatering process of oil sands MFT. However, simulated runoff or seepage waters from chemically amended and dried MFT were phytotoxic, due to combined levels of salts, naphthenic acids and pH. Phytoremediation of runoff water/ground water seepage from dry-land applied MFT will thus require pre-treatment in order to make conditions more favorable for plant growth.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.775
Threshold uncertainty score0.215

Codex and Gemma teacher scores by category

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 head0.012
GPT teacher head0.242
Teacher spread0.230 · 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.

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

Citations26
Published2010
Admission routes1
Has abstractyes

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Same venueJournal of Environmental Science and Health Part ASame topicHydrocarbon exploration and reservoir analysisFrench-language works237,207