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Record W4293197413

Amélioration de la qualité des semences : des travaux de recherche qui portent fruit

2007· preprint· en· W4293197413 on OpenAlexaboutno aff
Fabienne Colas, M. Bettez, Patrick Baldet, A. Savary, Marie-Odile Perron, Denise Tousignant

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2007
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicSeed Germination and Physiology
Canadian institutionsnot available
Fundersnot available
KeywordsQuality (philosophy)Computer scienceEpistemologyPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

In Quebec, among its mandates, the MRNF develops operational techniques of forest seeds production. It also manages the single centre of forest seeds of Québec. The Direction of Forest Research (DRF) works complementarily with the Direction of the Production of Seeds and Seedlings (DPSP) in order to improve the seed processing sector technology. The work concerns in particular the installation of the seed orchards and the improvement of the processes in the Centre of Forest Seeds of Berthier (CSFB) in order to provide good quality seeds to the 24 forest nurseries of Quebec. The research projects carried out by the DRF generated innovations now in operation in the seed orchards and the nurseries of Quebec. We will draw up an evaluation of the achievements: improvement of the genetic quality of the seeds produced in seed orchard; development of the first sheltered orchard specifically designed for the production of hybrid seeds of larch; optimization of the quantity of seeds provided for the production of seedlings. The quality improvement of seeds extracted by the CSFB is a continuous process which already allowed a significant increase in the germination rate of seed lots since 2003. The measurement of the Activity of Water (Aw), method used in the food industry, will be the purpose of new research, undertaken thanks to a scientific collaboration between the DRF and the Cemagref of Nogent-sur-Vernisson (France). This project will lead to the improvement of the quality of seeds and to their preservation. / Au Québec, parmi ses mandats, le MRNF développe les techniques opérationnelles de production des semences forestières. Il gère également l'unique centre de semences forestières québécois. La Direction de la recherche forestière (DRF) travaille en complémentarité avec la Direction de la production des semences et des plants (DPSP) afin d'améliorer la filière technologique des semences. Les travaux portent notamment sur l'aménagement des vergers à graines et l'amélioration des procédés au Centre de semences forestières de Berthier (CSFB) afin de fournir des semences de qualité pour les 24 pépinières forestières du Québec. Les projets de recherche menés à la DRF ont généré des innovations maintenant intégrées aux opérations dans les vergers à graines et les pépinières du Québec. Nous dresserons un bilan des réalisations : amélioration de la qualité génétique des semences produites en verger à graines; mise au point du tout premier verger sous abri spécifiquement destiné à la production de graines de mélèze hybride; optimisation de la quantité de graines fournies pour la production de plants . L'amélioration de la qualité des graines extraites au CSFB est un processus continu qui a déjà permis une augmentation significative de la germination des lots depuis 2003. La mesure de l'activité de l'eau (Aw), méthode utilisée dans l'industrie agro-alimentaire, fera l'objet d'une nouvelle initiative de recherche, menée grâce à une collaboration scientifique entre la DRF et le Cemagref de Nogent-sur-Vernisson (France). Ce projet va conduire à l'amélioration de la qualité des semences et à leur conservation.

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)0.020
metaresearch head score (Gemma)0.008
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: Other · Consensus signal: none
Teacher disagreement score0.329
Threshold uncertainty score0.655

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.008
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.003
Science and technology studies0.0020.004
Scholarly communication0.0060.003
Open science0.0020.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.105
GPT teacher head0.330
Teacher spread0.225 · 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
GenreOther

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
Published2007
Admission routes1
Has abstractyes

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