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Record W2109645979 · doi:10.13052/jge1904-4720.421

Green Energy Production:The Potential of Using Biomass Gasification

2014· article· en· W2109645979 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Green Engineering · 2014
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsMcGill University
Fundersnot available
KeywordsBiomass (ecology)Production (economics)Environmental scienceBiomass gasificationWaste managementProcess engineeringBiochemical engineeringPulp and paper industryAgricultural engineeringEngineeringAgronomyBiologyEconomics

Abstract

fetched live from OpenAlex

Biomass gasification shows a great potential to displace fossil fuels. In this paper, the potential of bioenergy production from biomass feedstock has been investigated, focusing on gasification technology as an environmentally friendly alternative. The present research is principally focused on a down draft gasifier equipment kit (GEK) unit. Biomass encompasses a wide range of feedstocks such as agricultural residues, energy crops, forestry materials, food waste, municipal solid waste, grains and starch crops. An efficient gasification unit produces syngas with calorific value up to 20 MJ/kg. Syngas predominately consists of a mixture of hydrogen and carbon monoxide. This syngas can be used in a number of different processes including electricity generation, steam generation, transportation fuels, hydrogen production as well as chemical production, fertilizer manufacturing and consumer products. Results from our research highlight the potential of biomass gasification as a strong alternative for bioenergy production and a substitute for fossil fuels.

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.

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 score0.084
Threshold uncertainty score0.387

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 head0.007
GPT teacher head0.184
Teacher spread0.176 · 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