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Record W2042091043 · doi:10.1002/tox.20285

Phytotoxicity assay of crop plants to phenanthrene and pyrene contaminants in acidic soil

2007· article· en· W2042091043 on OpenAlexaff
Waraporn Chouychai, Amporn Thongkukiatkul, Suchart Upatham, Hung Lee, Prayad Pokethitiyook, Maleeya Kruatrachue

Bibliographic record

VenueEnvironmental Toxicology · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial bioremediation and biosurfactants
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPhenanthrenePyreneShootPhytotoxicityGerminationChemistrySoil contaminationAgronomyContaminationCropHorticultureEnvironmental chemistryBiologyOrganic chemistry

Abstract

fetched live from OpenAlex

Four selected plants (corn, groundnut, cow pea, and mungbean) were tested for their ability to germinate and grow in an acidic soil contaminated with phenanthrene or pyrene, two typical polycyclic aromatic hydrocarbons (PAHs). The growth of corn root was the least sensitive to, but its germination rate was the lowest in the presence of, contaminants. Among the legumes, the growth of groundnut root was better than others. Corn and groundnut were selected to further test their ability to tolerate a mixture of phenanthrene and pyrene in the acidic soil. The presence of both PAHs led to a greater decrease in the lengths of shoot and root of groundnut than phenanthrene or pyrene alone, but the lengths of shoot and root of corn were decreased to a similar extent as when phenanthrene or pyrene was present alone. The growth of corn root was also better than that of groundnut root when they were grown in oil-contaminated soil. Based on these results, we conclude that corn is the most suitable to be grown in PAH-contaminated acidic soil.

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 score0.006

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.008
GPT teacher head0.225
Teacher spread0.217 · 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

Citations31
Published2007
Admission routes1
Has abstractyes

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