MétaCan
Menu
Back to cohort
Record W2404145361 · doi:10.4000/vertigo.17282

Structure, composition spécifique et diversité des ligneux dans deux zones contrastées en zone Sahélienne du Burkina Faso

2016· article· fr· W2404145361 on OpenAlexvenueno aff
Ouango Maurice Savadogo, Korodjouma Ouattara, Souleymane Paré, Issa Ouédraogo, Séraphine Sawadogo-Kaboré, Jennie Barron, Nabsanna Prosper Zombré

Bibliographic record

VenueVertigO · 2016
Typearticle
Languagefr
FieldAgricultural and Biological Sciences
TopicAfrican Botany and Ecology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsForestryGeographyHumanitiesArt

Abstract

fetched live from OpenAlex

Cette étude menée au Sahel burkinabé fait l’état actuel de la végétation ligneuse de cette région afin d’établir le lien entre la réalité du terrain et les observations satellitaires dans deux sites dans chacune des deux zones contrastées, l’une présentant un certain taux de reverdissement et l’autre de dégradation. Elle analyse aussi la composition spécifique, la structure, la diversité des ligneux et les similitudes entre les quatre sites (deux sites par deux zones). L’étude a utilisé une méthode d’échantillonnage stratifiée aléatoire analysant 104 placettes de 20 x 20 m². L’analyse statistique a montré des différences significatives de la densité, du nombre d’espèces, de la classe des hauteurs, de la classe des diamètres et des indices de Simpson et Shannon entre les deux zones. Les valeurs les plus importantes ont été observées dans la zone en reverdissement. Nous avons noté aussi une différence significative de la densité, des diamètres et des hauteurs en fonction de l’occupation des terres. Les champs de la zone en reverdissement possèdent les valeurs les plus importantes de densité et des hauteurs, mais ont les diamètres les moins élevés. Le reverdissement au Sahel est donc plus apparent dans les champs.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.045
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.201
Teacher spread0.189 · 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

Citations16
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueVertigOSame topicAfrican Botany and Ecology StudiesFrench-language works237,207