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Record W2161913410 · doi:10.2980/15-4-3156

Effect of cold exposure on seed germination of 58 plant species comprising several functional groups from a mid-mountain Mediterranean area

2008· article· en· W2161913410 on OpenAlexvenueno aff
Belén Luna, Beatriz Pérez, Blanca Céspedes, José M. Moreno

Bibliographic record

VenueEcoscience · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSeed Germination and Physiology
Canadian institutionsnot available
FundersEuropean Commission
KeywordsGerminationStratification (seeds)Mediterranean climateDormancyPeninsulaSeed dormancyBiologyEndemismBotanyEcologyHorticulture

Abstract

fetched live from OpenAlex

The effects of cold stratification on seed germination of 58 species from a Mediterranean area in central—eastern Spain were studied. The area is subject to fires and has a very continental climate, with long winters (187 frost days during the year). Differences in germination among species taking into account their phylogeny were studied by dividing them according to their life form (chamaephytes, hemicryptophytes), post-fire regeneration strategy (non-sprouters, sprouters), and geographical distribution range (Iberian Peninsula endemics, Mediterranean, widely distributed species). Treated seeds were stratified at 5 °C for 4 weeks, then incubated, along with the control seeds, at 15 °C for 6 weeks. Most species were not affected by cold stratification, and in the cases where they were, germination was generally lower after stratification, not higher. In general, germination percentages were low, which shows that stratification by itself was not able to break seed dormancy. Functional groups differing in their post-fire regenerative strategy or distribution range showed differing responses. Sprouters and endemic species from the Iberian Peninsula were negatively affected by stratification treatment. This is interpreted as a mechanism to stop germination after winter, preventing plants from late germination in spring, which would leave them facing summer drought without a deeply developed root system.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.808
Threshold uncertainty score0.399

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.030
GPT teacher head0.222
Teacher spread0.192 · 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

Citations21
Published2008
Admission routes1
Has abstractyes

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