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Record W2471975875

REDUCTION DE L'IMPACT SUR L'EFFET DE SERRE PAR L'ECO-CONCEPTION DES CAVES: CONTEXTE ET APPLICATION

2010· article· fr· W2471975875 on OpenAlexaboutno aff
Jean-Francois Rochard, C Vallet, Pascal. Auteur du texte Labbé

Bibliographic record

VenueBulletin de l'OIV · 2010
Typearticle
Languagefr
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt
DOInot available

Abstract

fetched live from OpenAlex

La construction d'un bâtiment viticole ou d'une cave et le choix des equipements associes a la conception des equipements de l'ouvrage suppose une reflexion approfondie concernant notamment les aspects economiques, qualitatifs, la securite des utilisateurs. Au-dela de I'aspect fonctionnel, la prise en compte du developpement durable impose une reflexion relative a l'impact de la conception et du fonctionnement des caves sur l'effet de serre. Autrefois tous les moyens naturels qui permettaient de beneficier de la fraicheur ou de la chaleur etaient utilises La conception des bâtiments, associant une bonne isolation eventuellement completee de solutions originales (toits ou murs vegetalises, puits canadiens...) et les energies alternatives (solaire, geothermie, biomasse...) s'integre dans cette dynamique de conception ecologique des caves. Ces aspects, ainsi que l'integration paysagere contribue a valoriser l'image environnementale de la cave. Des demarches originales pionnieres, peuvent s'integrer, au-dela des choix architecturaux, dans une demarche de communication et de valorisation des vins. Par ailleurs, la reglementation, les normes evoluent au cours des prochaines annees, ce qui justifie d'anticiper les exigences environnementales, afin d'eviter des modifications de mise aux normes couteuses.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.033
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0050.002
Open science0.0020.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0150.001

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 head0.260
Teacher spread0.250 · 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 designNot applicable
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

Citations0
Published2010
Admission routes1
Has abstractyes

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