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Record W2746116040 · doi:10.3390/f8090305

Can Biomass Quality Be Preserved through Tarping Comminuted Roadside Biomass Piles?

2017· article· en· W2746116040 on OpenAlexafffund
Suzanne Wetzel, Sylvain Volpé, Janet Damianopoulos, Sally Krigstin

Bibliographic record

VenueForests · 2017
Typearticle
Languageen
FieldEngineering
TopicForest Biomass Utilization and Management
Canadian institutionsFPInnovationsUniversity of TorontoCanadian Wood Council
FundersNatural Resources Canada
KeywordsBiomass (ecology)Environmental scienceBiorefiningBioenergyPulp and paper industryRaw materialWater contentBiorefineryRenewable energyAgronomyEcologyBiology

Abstract

fetched live from OpenAlex

Storage conditions play a vital role in maintaining biomass quality as a suitable bioenergy feedstock. Research has shown that biomass undergoes significant changes under different storage conditions and that these may influence its suitability for various biorefining and bioenergy opportunities. This study explores the effects of different tarp covers on the properties of stored-comminuted forest harvest residue from the Great Lakes St. Lawrence Forest. Characteristics of the biomass were evaluated upon harvesting and after one year in storage. The physical state of the different tarps used for pile coverage was monitored onsite. Results indicated that tarp material considerably affects micro-climatic conditions inside piles, yielding variation in the characteristics of stored biomass over the storage period. While plastic based tarps were easier to work with and lasted longer than paper-based tarps, the paper-based tarps were more breathable and resulted in less degradation of biomass. However, the paper-based tarps did not maintain their structural integrity for the full duration of the storage period. Moisture content of original biomass (48.99%) increased to a maximum of 65.25% under plastic cover after 1 year of storage. This negatively influenced the net heating value of the biomass, causing it to decrease from 8.58 MJ/kg to 4.06 MJ/kg. Overall, the use of covers was not considered successful in preserving the original quality of biomass but may enhance its quality for other biorefinery opportunities.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 communication0.0010.000
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 head0.068
GPT teacher head0.308
Teacher spread0.240 · 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 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

Citations19
Published2017
Admission routes2
Has abstractyes

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