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Record W2020399801 · doi:10.4236/epe.2013.52a006

Harvest of Short-Rotation Woody Crops in Plantations with a Biobaler

2013· article· en· W2020399801 on OpenAlexafffund
Philippe Savoie, Pierre-Luc Hébert, François-Simon Robert, Derek Sidders

Bibliographic record

VenueEnergy and Power Engineering · 2013
Typearticle
Languageen
FieldEngineering
TopicForest Biomass Utilization and Management
Canadian institutionsNatural Resources CanadaMinistère de l'Agriculture, des Pêcheries et de l'AlimentationUniversité LavalCanadian Forest ServiceAgriculture and Agri-Food Canada
FundersNatural Resources CanadaCanadian Forest ServiceAgriculture and Agri-Food CanadaU.S. Forest Service
KeywordsEnvironmental scienceBiomass (ecology)BioenergyUnderstoryWoody plantAgroforestryAgronomyMulchBiofuelMathematicsEngineeringWaste managementCanopyBotanyBiology

Abstract

fetched live from OpenAlex

The biobaler is an alternative to the modified self-propelled forage harvester to cut and collect short rotation woody crops (SRWC). It is less capital intensive and more versatile, being able to harvest woody crops on plantations, on abandoned farmland, on brush land or within forest understory. The biobaler was evaluated specifically on five different plantations over 19 experimental units (546 bales harvested with an average mass of 427 kg and 49% moisture content). Average bale density was 266 kg wet mass (WM)/m3 or 139 kg dry mass (DM)/m3. Average harvest capacity was 35 bales/h (7.7 t dry matter/h), and ranged from 23 to 48 bales/h. Harvest in plantations with a 149 kW tractor cost on average CAN $175/h, $5/bale and $22.84/t DM. Non recovered biomass (field loss) averaged 11% at random locations in the field and 8% at the point of bale ejection as a result of chip abrasion. While the biobaler remains a versatile harvester for SRWC, its preferred utilization will be in environments of diverse woody crops with final application as a rough mulch or for combustion in furnaces requiring minimal processing or size reduction.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.004
GPT teacher head0.166
Teacher spread0.162 · 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

Citations16
Published2013
Admission routes2
Has abstractyes

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