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Record W3121783176 · doi:10.54966/jreen.v16i3.395

Etude du potentiel de biomasse forestière en vue du développement des filières bois énergie en Algérie

2023· article· fr· W3121783176 on OpenAlexaboutno aff
Saliha Haddoum, Abdelkader Rahmani, Racha Rahil Ben Brahim, Ouahid Zanndouche, Toudert Ahmed Zaïd

Bibliographic record

VenueJournal of Renewable Energies · 2023
Typearticle
Languagefr
FieldEngineering
TopicForest Biomass Utilization and Management
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceForestryPhysicsEnvironmental scienceHumanitiesGeographyArt

Abstract

fetched live from OpenAlex

Ce travail est une réflexion sur les possibilités de valorisation des déchets forestiers pour le développement des filières de bois énergie utilisant la technique de cogénération. Outre les impacts bénéfiques sur l’environnement, ces filières de bois énergie peuvent avoir des retombées socio-économiques qui pourraient contribuer au développement durable de régions désenclavées à l’intérieur du pays. Partant d’un inventaire forestier établi en 2007, nous avons simulé une filière en optant pour la cogénération en tant que procédé de transformation accessible et adapté au ‘portrait biomasse’ de l’Algérie, consolidé par une étude technico-économique très sommaire d’une centrale électrique de cogénération utilisant la biomasse comme combustible. La simulation a été faite au moyen du logiciel RETScreen développé par le gouvernement canadien pour encourager l’implantation de projets d’énergie renouvelable.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.233
Teacher spread0.222 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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Same venueJournal of Renewable EnergiesSame topicForest Biomass Utilization and ManagementFrench-language works237,207