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Record W1929531495

Flétrissement et pourriture racinaire de la lentille dans le nord-ouest algérien

2001· article· fr· W1929531495 on OpenAlexaboutno aff
L. Belabid, Zohra Fortas, Daniele Dalli, M. Khiare, D. Amdjad

Bibliographic record

VenueCahiers Agricultures · 2001
Typearticle
Languagefr
FieldAgricultural and Biological Sciences
TopicAgronomic Practices and Intercropping Systems
Canadian institutionsnot available
Fundersnot available
KeywordsForestryBiologyFusarium oxysporumArtHorticultureGeography
DOInot available

Abstract

fetched live from OpenAlex

Les legumineuses alimentaires representent une part importante de l’alimentation humaine et animale. Ces cultures sont riches en proteines et fournissent au sol une quantite non negligeable d’azote fixe utile pour les cereales, en reduisant d’autant les couts de production et en limitant la pollution des nappes phreatiques par les nitrates des engrais [1]. En Algerie, la superficie cultivee en lentille (Lens culinaris Med.) est passee de 26 000 ha en 1969 a 1 500 ha en 1997, avec des rendements fluctuants qui demeurent tres faibles [2]. Les champignons telluriques constituent un des principaux facteurs limitant le developpement de la lentille, causant des maladies de fletrissement ou de pourriture racinaire notamment en Egypte [3], en Syrie [4], au Canada [5], en Tchecoslovaquie [6] et Nouvelle-Zelande [7]. Les agents responsables de ces maladies, en particulier de la pourriture racinaire, appartiennent aux genres Rhizoctonia, Fusarium, Thielaviopsis, Macrophomina, Ozonium, Pythium, Aphanomyces et Sclerotinia [8]. Quant au fletrissement vasculaire, il est provoque par F. oxysporum [4]. L’objectif de notre etude est d’evaluer l’importance de ces maladies et d’identifier les especes fongiques responsables, ainsi que la frequence de leur repartition dans le nord-ouest algerien. Le pouvoir pathogene des isolats de F. oxysporum isoles de lentille a ete teste par ailleurs.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.150
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.009
GPT teacher head0.245
Teacher spread0.236 · 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.

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

Citations7
Published2001
Admission routes1
Has abstractyes

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