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Record W4408254019 · doi:10.4000/13fab

Le devenir des bandes boisées du haut plateau de l’Aubrac

2024· article· fr· W4408254019 on OpenAlexaff
Rémy Teyssèdre

Bibliographic record

VenueProjets de paysage · 2024
Typearticle
Languagefr
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsÉcole Nationale d'Administration Publique
Fundersnot available
KeywordsArtPolitical science

Abstract

fetched live from OpenAlex

Les bandes boisées, plantées de résineux, sont des ouvrages de génie végétal remontant pour la plupart à la seconde moitié du xxe siècle. Situées le long du réseau viaire, elles visent à lutter contre les congères fréquentes sur le haut plateau de l’Aubrac au climat neigeux et tempétueux, ainsi qu’à abriter les troupeaux bovins. Elles sont devenues, au fil des années, un motif paysager structurant de ce territoire agropastoral. Plusieurs dynamiques – en premier lieu, leur vieillissement – mènent aujourd’hui ces plantations au dépérissement et à leur arrachage. Par un regard historique sur ces plantations et leur prise en compte par les acteurs institutionnels et socio-économiques, l’article met en évidence les rôles du paysage dans une démarche d’acclimatation : marqueur visuel, signal, objet de controverse, mais aussi de projection. Il revient sur l’action publique déployée par le parc naturel régional de l’Aubrac pour sauvegarder, transformer et adapter ces plantations aux enjeux futurs. L’analyse de cette expérience permet également de formuler les opportunités qu’offre le paysage, en tant qu’objet de médiation.

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 score0.239
Threshold uncertainty score0.476

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 studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.031
GPT teacher head0.269
Teacher spread0.238 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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