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Record W2035974738 · doi:10.1080/09593330.2004.9619375

Growth of Water Hyacinth in Municipal Landfill Leachate with Different pH

2004· article· en· W2035974738 on OpenAlex

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEnvironmental Technology · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicConstructed Wetlands for Wastewater Treatment
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsHyacinthEichhornia crassipesLeachateEnvironmental scienceEnvironmental chemistryEnvironmental engineeringWindsorChemistryAquatic plantPulp and paper industryMacrophyteEcologyBiology

Abstract

fetched live from OpenAlex

Batch experiments were conducted to investigate the effect of municipal landfill leachate pH on the growth of water hyacinth (Eichhornia crassipes). These experiments were carried out in a green house environment on leachate samples collected from Essex-Windsor Regional Landfill, Windsor, Ontario, Canada. It was found that water hyacinth plants survived in a pH range of 4.0 to 8.0. Both alkaline pH (above 8.0) and highly acidic pH (below 4.0) had inhibitory effect on the growth of plants. The pH range, for optimum growth of the water hyacinth plants was found to be 5.8 to 6.0. At optimum growth, water hyacinth had an average mean relative growth rate of 0.043 d-1. It was found that nitrogen compounds underwent different transformations depending on the pH of leachate. Plant uptake, nitrification and volatilization were among these transformations.

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)0.000
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 score0.692
Threshold uncertainty score0.950

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 studies0.0000.001
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 head0.004
GPT teacher head0.169
Teacher spread0.166 · 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