MétaCan
Menu
Back to cohort
Record W2011752868 · doi:10.4000/vertigo.13176

Mise en œuvre opérationnelle d’un projet de compensation carbone de foyers améliorés au Niger

2013· article· fr· W2011752868 on OpenAlexvenueno aff
Fanny Joubert, Miléna Bégovic

Bibliographic record

VenueVertigO · 2013
Typearticle
Languagefr
FieldEnvironmental Science
TopicEnergy and Environment Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceForestryHumanitiesGeographyArt

Abstract

fetched live from OpenAlex

L’utilisation de foyers « ouverts » traditionnels utilisés au Niger a de lourdes conséquences au niveau environnemental, sanitaire et économique. Le projet de compensation carbone de foyers améliorés présenté ici consiste à remplacer ces foyers traditionnels par des foyers améliorés plus performants (appelés Kiva-Hybride) permettant de réduire la consommation de bois d'origine non renouvelable. La mise en œuvre d’un tel projet nécessite un travail préalable conséquent afin d’assurer sa pérennité sur le terrain : études statistiques, élaboration de différents prototypes de foyers avec tests de performance énergétique, réunions de consultations publiques avec les parties prenantes. Répondant à la méthodologie Gold Standard, ce projet permet non seulement de réduire les émissions de gaz à effet de serre à l’échelle mondiale, mais aussi d’améliorer les conditions de vie des populations locales (lutte contre la déforestation, amélioration de la qualité de l’air intérieur, économies des dépenses et de temps liés à la collecte du bois). En effet, le Kiva-Hybride permet de réduire les besoins en bois d’environ 1,5 tonne/foyer/an en moyenne conduisant à 2,79 teqCO2 d’émissions évitées par an et à l’économie de 47 500 FCFA/an par ménage.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.359
Threshold uncertainty score1.000

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.004

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 head0.207
Teacher spread0.197 · 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; both teacher heads agree on what is shown here.

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

Citations2
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueVertigOSame topicEnergy and Environment ImpactsFrench-language works237,207