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Record W2137154582 · doi:10.1093/aob/mch074

Microgeographic Genome Size Differentiation of the Carob Tree, Ceratonia siliqua, at 'Evolution Canyon', Israel

2004· article· en· W2137154582 on OpenAlexfundno aff
Petr Bureš

Bibliographic record

VenueAnnals of Botany · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPolysaccharides Composition and Applications
Canadian institutionsnot available
FundersOttawa Hospital Research Institute
KeywordsCeratonia siliquaBiologyCanyonGenome sizeEvergreenBotanyGenomeGeneGenetics

Abstract

fetched live from OpenAlex

BACKGROUND AND AIMS: We tested whether the local differences in genome size recorded earlier in the wild barley, Hordeum spontaneum, at 'Evolution Canyon', Mount Carmel, Israel, can also be found in other organisms. As a model species for our test we chose the evergreen carob tree, Ceratonia siliqua. METHODS: Genome size was measured by means of DAPI flow cytometry. KEY RESULTS: In adults, significantly more DNA was recorded in trees growing on the more illuminated, warmer, drier, microclimatically more fluctuating 'African' south-facing slope than in trees on the opposite, less illuminated, cooler and more humid, 'European' north-facing slope in spite of an interslope distance of only 100 m at the canyon bottom and 400 m at the top. The amount of DNA was significantly negatively correlated with leaf length and tree circumference. In seedlings, interslope differences in the amount of genome DNA were not found. In addition, the first cases of triploidy and tetraploidy were found in C. siliqua. CONCLUSIONS: The data on C. siliqua at 'Evolution Canyon' showed that local variability in the C-value exists in this species and that ecological stress might be a strong evolutionary driving force in shaping the amount of DNA.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.226
Teacher spread0.207 · 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

Citations36
Published2004
Admission routes1
Has abstractyes

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