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Record W2967144136 · doi:10.3390/su11164394

Pulp and Paper Mill Fly Ash: A Review

2019· review· en· W2967144136 on OpenAlexafffund
Chinchu Cherian, Sumi Siddiqua

Bibliographic record

VenueSustainability · 2019
Typereview
Languageen
FieldEarth and Planetary Sciences
TopicCoal and Its By-products
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersMitacs
KeywordsFly ashPaper millPulp (tooth)Waste managementEnvironmental sciencePulp millMillEngineeringPulp and paper industry

Abstract

fetched live from OpenAlex

The continual growth of pulp and paper industry has led to the generation of tremendous volumes of fly ash as byproducts of biomass combustion processes. Commonly, a major part of it is landfilled; however, updated environmental regulations have tended to restrict the landfilling of fly ash due to rising disposal costs and the scarcity of suitable land. The pulp and paper industries are therefore urgently seeking energy-efficient mechanisms and management for the beneficial use of fly ash in an ecological and economical manner. This paper offers a comprehensive review of existing knowledge on the major physicochemical and toxicological properties of pulp and paper mill fly ash to assess its suitability for various bound and unbound applications. The current state of various methods used for the valorization of pulp and paper mill fly ash into more sustainable geomaterials is briefly discussed. This paper also presents promising and innovative applications for pulp and paper mill fly ash, with particular reference to agriculture and forestry, the construction and geotechnical industries, and the immobilization of contaminants. It was identified from a literature review that modified pulp and paper mill fly ash can be environmentally and economically advantageous over commercial coal-based fly ash in various sustainable applications.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Other designhigh
models splitAgreement compares identical category sets and study designs across arms.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.036
GPT teacher head0.294
Teacher spread0.258 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designNot applicable · Other design
Domainnot available
GenreReview

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

Citations74
Published2019
Admission routes2
Has abstractyes

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