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Record W4293198678

Water activity measurement: demonstration of a single and nonspecific optimal storage value for orthodox forest seeds

2010· preprint· en· W4293198678 on OpenAlexaffabout
Fabienne Colas, Patrick Baldet, M. Bettez

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2010
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicIrrigation Practices and Water Management
Canadian institutionsMinistère des Ressources naturelles et des Forêts (Québec)
Fundersnot available
KeywordsValue (mathematics)Water storageEnvironmental scienceComputer scienceMathematicsStatisticsEngineeringMechanical engineering
DOInot available

Abstract

fetched live from OpenAlex

Water activity (aw) is a non destructive, portable and rapid technique to assess moisture of hygroscopic materials like orthodox seeds. aw, as equilibrium Relative Humidity (eRH), is a reliable moisture indicator because it is a function of the water potential (Ψ) which portrays the energy status of water in hygroscopic matrixes.\nCemagref (France) demonstrated the efficiency of aw applied to moisture management of major temperate forest orthodox seeds. Since 2007, in cooperation with Cemagref, the Ministère des Ressources naturelles et de la Faune du Québec decided to verify that aw is also efficient with orthodox boreal species. The three major species of the Québec's reforestation program, representing 95% of the 470 millions seeds used in 2009, were characterized through the production of sorption isotherms. These isotherms allowed to describe the moisture behaviour of the seeds and to determine the optimal aw value for storage. All the results follow the same pattern obtained formerly in France. aw is now successfully used in France and Québec tree seed centres. Thanks to the numerous sorption isotherms data on the different species, it appears that every optimal storage value obtained for each orthodox species, always ranges in the region of aw 0.35 (140 MPa water potential). We assume that this value could be profitably used as a universal target for moisture management of diverse orthodox reproductive material in gene banks where it is not operationally possible to determine optimal gravimetric moisture content for mid to long-term storage due to the samples size.

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)0.005
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.452

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.037
GPT teacher head0.222
Teacher spread0.185 · 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 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

Citations0
Published2010
Admission routes2
Has abstractyes

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