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Record W4293198497

Water activity - An efficient tool for seed testing

2009· preprint· en· W4293198497 on OpenAlexaff
Patrick Baldet, Fabienne Colas, M. Bettez

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2009
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicSoybean genetics and cultivation
Canadian institutionsMinistère des Ressources naturelles et des Forêts (Québec)
Fundersnot available
KeywordsEnvironmental scienceAgricultural engineeringComputer scienceEngineering
DOInot available

Abstract

fetched live from OpenAlex

Water activity (aw) is a non destructive, portable and a rapid technique currently used to assess the moisture of hygroscopic materials (e.g. agro-food, pharmaceutical) and particularly, the one of intermediate products such as orthodox seeds . This technique (aw), as well as equilibrium Relative Humidity (eRH), is a reliable moisture indicator because it is directly related to the water potential (Ψ), which indicates the energy status of water in hygroscopic matrixes. While gravimetric moisture content (GMC) quantifies only the total amount of water in a product, aw qualifies the intensity of the bonds between water and other molecules (e.g. lipids, carbohydrates or proteins) and therefore, it illustrates the water availability and mobility within a substance. Water activity (aw) has three main advantages : this technique is rapid (less than 20 min per sample), non destructive (very interesting for small samples of great value such as seeds for ex situ genetic conservation), and easy to use (light training required). / La mesure de l'Activité de l'eau (aw) est un essai non destructif, portable et rapide actuellement utilisé pour évaluer l'état hydrique des matériaux hygroscopiques (p. ex., agro-alimentaire, pharmaceutique) et en particulier, les produits à humidité intermédiaire tels que les semences orthodoxes. Cette technique (aw), de même que " humidité relative d'équilibre " (HRE), est un indicateur d'humidité fiable car il est directement lié au potentiel de l'eau (Ψ), lequel indique l'état de l'énergie de l'eau dans les matrices hygroscopiques. Alors que le taux d'humidité gravimétrique (GMC) quantifie uniquement la quantité totale d'eau dans un produit, l' aw qualifie l'intensité des liens entre l'eau et les autres molécules (p. ex., lipides, glucides ou protéines) et, par conséquent, illustre la disponibilité et la mobilité de l'eau au sein d'une substance. L'activité d'eau (aw) possède trois principaux avantages : cette mesure est rapide (moins de 20 mn par échantillon), non destructive (très intéressante pour les petits échantillons de grande valeur comme les graines de conservation ex situ de ressources génétiques) et facile à utiliser (formation requise très limitée).

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.004

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 head0.029
GPT teacher head0.228
Teacher spread0.199 · 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

Citations2
Published2009
Admission routes1
Has abstractyes

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