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Record W4241527552 · doi:10.24124/2014/bpgub1612

Ash management at Canfor Pulp - turning a waste product into a profit stream

2014· dissertation· en· W4241527552 on OpenAlexaff
James Allan Spankie

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicCoal and Its By-products
Canadian institutionsUniversity of ReginaUniversity of Northern British Columbia
Fundersnot available
KeywordsLand reclamationWaste managementReuseProfit (economics)Pulp (tooth)Net profitEnvironmental sciencePulp and paper industryEngineeringBusinessAgricultural economicsEconomicsGeographyArchaeology

Abstract

fetched live from OpenAlex

Canfor Pulp Ltd. produces bleached and unbleached softwood Kraft Pulp and Paper products at mills located in Prince George British Columbia. They burn biomass to generate energy, and they produce ash as a by-product. Due to the changing nature of the business, the amount of waste ash produced by Canfor Pulp has increased significantly over the last 10 years - using conservative estimates, by at least 100%. This project examined the options available for beneficial reuse of the ash, measured them against defined criteria in order to select preferred options and then and evaluated the viability of those options for the diversion and sale of this ash. It was determined that use of the ash as an agricultural supplement presents a viable market for the ash. Market size and price are not barriers to enter into this market. Other markets, such as mine reclamation, and petroleum site reclamation may also be viable outlets for the ash, pending the outcome of further financial analysis. --Leaf 1.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.050
Threshold uncertainty score0.168

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0500.013

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 head0.009
GPT teacher head0.211
Teacher spread0.201 · 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
Published2014
Admission routes1
Has abstractyes

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