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Record W2125214656 · doi:10.1139/a03-001

Modeling the role of papermill sludge in the organic carbon cycle of paper products

2003· article· en· W2125214656 on OpenAlexaffvenue
Warren Mabee, Dipankar Roy

Bibliographic record

VenueEnvironmental Reviews · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Impact and Sustainability
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPaperboardEnvironmental scienceWaste managementSewage sludgeCarbon cycleCarbon fibersLife-cycle assessmentPulp and paper industrySewage treatmentProduction (economics)Environmental engineeringEngineeringEcologyEcosystemBiologyMaterials science

Abstract

fetched live from OpenAlex

Fundamental information about the chemistry of sludge, published rates of sludge generation, and models of paper production and wastepaper recycling were combined to create a predictive model. The goal of the modeling exercise was to determine and project global sludge production until the year 2050. It was predicted that a global shift in paper and paperboard production would result in the Asia-Pacific region emerging as a major producer of papermill sludge. Global production of papermill sludge was predicted to rise over the next 50 years by between 48 and 86% over current levels. Sludge was found to contain a large amount of woody organic material, but the proportion of this material in the sludge was found to drop as recycling programs were implemented. Sludge was also found to contain a large amount of woody carbon, which comprised about 30% of the total sludge solids. The presence of such a large proportion of woody carbon may become important if a system of carbon crediting is implemented for the forest industry. Key words: carbon cycle, forests, papermill sludge, modeling, life cycle analysis.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.451
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0010.000

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 head0.009
GPT teacher head0.219
Teacher spread0.209 · 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.

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

Citations28
Published2003
Admission routes2
Has abstractyes

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