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Record W2044021166 · doi:10.4000/vertigo.2221

Production de biogaz et de compost à partir de eichhornia crassipes, (mart) solms-laub (pontederiaceae) pour un développement durable en Afrique sahélienne

2006· article· fr· W2044021166 on OpenAlexvenueno aff
O. Almoustapha, J. Millogo‐Rasolodimby

Bibliographic record

VenueVertigO · 2006
Typearticle
Languagefr
FieldAgricultural and Biological Sciences
TopicBiological Control of Invasive Species
Canadian institutionsnot available
Fundersnot available
KeywordsEichhornia crassipesBiologyEcologyAquatic plant

Abstract

fetched live from OpenAlex

Dans le parc urbain Bangré-Weoogo de la commune de Ouagadougou (Burkina Faso) la prolifération de la jacinthe d’eau menace la conservation de la biodiversité. L’application de la lutte intégrée n’a pas permis de l’éradiquer. L’objectif de l’étude est de contribuer à la mise en place d’un protocole de gestion de Eichornia crassipes qui associe à la lutte mécanique la valorisation par la production de biogaz et de compost. Les résultats montrent une importante production de biomasse avec une proportion de matière sèche de 6,12 %. Les expérimentations, menées avec des digesteurs de type discontinu de 200 litres de capacité avec pour substrat 60 kg de la jacinthe d’eau ensemencée avec 20 litres de purin de bactéries méthanogènes indique une production moyenne de biogaz de 1440 litres de bio gaz pour 3,67 kg de matière sèche de jacinthe, soit 392,37 litres /kg/ MS. L’analyse chimique a montré que le compost issu de ces expérimentations contient, entre autre 9,930 kg de phosphore total, et 0,690 kg d’ortho-phosphate, 6,27 kg d’azote Kjeldahl par tonne de compost. L’application de cette technologique dans les zones humides infestées par E. crassipes présente plusieurs avantages : production d’énergie, de compost et contrôle de la prolifération de la jacinthe d’eau.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.665
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.230
Teacher spread0.215 · 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 teacher head, not a consensus.

Study designBench or experimental
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

Citations7
Published2006
Admission routes1
Has abstractyes

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Same venueVertigOSame topicBiological Control of Invasive SpeciesFrench-language works237,207