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Record W4239747257 · doi:10.24124/2011/bpgub1496

Costing the production of OSB using fibre impacted by mountain pine beetle

2011· dissertation· en· W4239747257 on OpenAlexaffabout
Patrick Smook

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicForest Biomass Utilization and Management
Canadian institutionsUniversity of AlbertaUniversity of Northern British Columbia
Fundersnot available
KeywordsOriented strand boardMountain pine beetleDeciduousActivity-based costingEngineeringEngineered woodHectareEnvironmental scienceForestryGeographyCivil engineeringBusinessEcology

Abstract

fetched live from OpenAlex

The current outbreak of mountain pine beetle (MPB) in western Canada has killed millions of hectares of pine forest, but has created the opportunity for oriented strand board (OSB) manufacturers to utilize this forest resource. However, MPB - killed timber is dry, porous and brittle, thus posing significant challenges at various stages of the OSB production process. These challenges include increases in breakage in timber harvesting, production of fine wood material at the stranding operation, wear on stranding blades, and resin use. In this study, a simulation of a western Canadian woodlands and OSB manufacturing process was constructed using the operations based costing framework. Once the simulation was constructed, expected impacts of MPB fibre were introduced to the model in a hypothetical scenario where a mixture of MPB and deciduous fibre were used in the manufacturing process to determine the overall cost impact of the alternative furnish mixture on cost of production. This analysis showed that for the subject operations, the use of a 28.8% mixture of MPB and deciduous furnish would yield 3.6% overall increase in the cost of finished OSB. To eliminate this cost gap, OSB manufacturers could investigate the economic viability of increasing ponds capacity, increasing ponds temperature, sale of excess fines material and alternative resination processes to allow inclusion of fines in finished product. --P. ii.

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 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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.146
Threshold uncertainty score0.483

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.236
Teacher spread0.222 · 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 teacher head, 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

Citations0
Published2011
Admission routes2
Has abstractyes

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