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Record W4234095641 · doi:10.32920/ryerson.14662815

Environmental Evaluation of Land-Applied Pulp Mill and Municipal Biosolids

2021· preprint· en· W4234095641 on OpenAlexaff
Ashley M Spearin

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsBiosolidsEnvironmental scienceIncinerationWaste managementPaper millAmendmentPulp (tooth)Pulp millMillSewage sludgeSewage treatmentEnvironmental engineeringEffluentEngineering

Abstract

fetched live from OpenAlex

In terms of disposal options, a form of waste that has received much attention in recent years is sludge, the by-product of wastewater treatment from both industrial and municipal sources. Negative issues associated with traditional sludge disposal practices (e.g. landfilling or incineration) have resulted in an increased interest to find disposal alternatives such as applying the sludge, or biosolids, to land as a soil amendment for purposes such as agriculture, horticulture, and silviculture. The objective of this study was to assess the environmental impact of pulp mill and municipal biosolids land-application using a suite of ecologically-relevant biota. Based on the results of this study, it can be concluded that the practice of pulp mill and municipal biosolids land-application may indeed be a viable and environmentally-sound alternative to other traditional disposal methods. This study did not detect any obvious impact on biota from pulp mill and municipal biosolids land-application and run-off into receiving-water when compared to reference bioassays.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.041
GPT teacher head0.228
Teacher spread0.186 · 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 designObservational
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

Citations0
Published2021
Admission routes1
Has abstractyes

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