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Record W2154097977 · doi:10.13031/2013.22062

ECONOMICS OF PELLET PRODUCTION FOR EXPORT MARKET

2006· article· en· W2154097977 on OpenAlexaboutno aff
Mozammel Hoque, Shahab Sokhansanj, Tony Bi, Sudhagar Mani, Ladan Jafari, Jim Lim, Parisa Zaini, Staffan Melin, Taraneh Sowlati, Muhammad T. Afzal

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicChemical and Environmental Engineering Research
Canadian institutionsnot available
Fundersnot available
KeywordsTonnePelletsPelletEconomic shortageAgricultural economicsInvestment (military)Production (economics)BusinessCapital investmentCapital costNatural resource economicsRaw materialEnvironmental scienceWaste managementEconomicsEngineeringFinance

Abstract

fetched live from OpenAlex

Due to its renewable, clean-burning and cost-stable for home heating, wood pellet is gaining popularity day by day throughout North America. The use of pellets in co-firing with coal enhanced its utilization suddenly in Europe. As a result, some countries in Europe are planning to import wood pellets from Africa, America or neighboring European countries due to the shortage of wood in long term basis. This study focuses on the pellet production in Canada and its export to Sweden or the Netherlands. The transport and supply logistics were analyzed. The results showed that the total production cost of pellets was US$46.8 per metric tonne and among which 4.5 US$/tonne was the capital investment. The transport and supply logistics cost estimated as US$ 96.1 or 89.1 per tonne for exporting to Sweden and the Netherlands, respectively. The internal rates of return for the two cases were estimated as 24 and 37%, respectively, with a plant life of 10 years and the payout periods of 4 and 3 years, respectively.

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)0.002
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: Other · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0300.002

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 head0.007
GPT teacher head0.184
Teacher spread0.177 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations24
Published2006
Admission routes1
Has abstractyes

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Same topicChemical and Environmental Engineering ResearchFrench-language works237,207