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Record W2165302408 · doi:10.1080/15226510903535072

Technical Note: Seeding Conditions of the Halophyte<i>Atriplex Patula</i>for Optimal Growth on a Salt Impacted Site

2011· article· en· W2165302408 on OpenAlexaffabout
Michelle Young, Doug G. Rancier, Julie Roy, Stuart Lunn, Sarah A. Armstrong, John V. Headley

Bibliographic record

VenueInternational Journal of Phytoremediation · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsUniversity of SaskatchewanEnvironment and Climate Change CanadaImperial Oil (Canada)
Fundersnot available
KeywordsHalophytePhytoremediationEnvironmental scienceSoil salinityAgronomySeedingPinus patulaSoil waterSalinityBiologyBotanyEcologySoil science

Abstract

fetched live from OpenAlex

Salt-impacted soils resulting from oilfield brine spills are increasingly becoming a significant problem in oil-producing areas of Canada such as Alberta and Saskatchewan. The native halophyte Atriplex patula is being considered a potential species for phytoremediation of brine-impacted sites in these hemiboreal climactic zones. The objective of this study was to investigate the optimal seeding conditions under field conditions (with no irrigation) of A. patula for phytoremediation of salt from a brine-impacted site. Atriplex patula was identified in preliminary greenhouse trials to have one of the highest salt accumulations in relation to plant yields. Different seeding methods of A. patula were assessed in an attempt to achieve reproducible growth of this species. While plant yields for A. patula were improved on compacted soil by approximately 30-50%, growth was uneven with regard to density and height. The uneven growth may be due to seed quality and low precipitation during the field season, while improvements in plant yield on compact soil might be due to a lack of competition with other species.

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)0.003
metaresearch head score (Gemma)0.002
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 score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.003

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 head0.014
GPT teacher head0.257
Teacher spread0.243 · 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

Citations14
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of PhytoremediationSame topicPeatlands and Wetlands EcologyFrench-language works237,207