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Record W2097073692 · doi:10.1093/aob/mcq236

The influence of cone age on the relative longevity of Banksia seeds

2010· article· en· W2097073692 on OpenAlexaff
Andrew Crawford, J. A. Plummer, Robin J. Probert, Kathryn J. Steadman

Bibliographic record

VenueAnnals of Botany · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSeed Germination and Physiology
Canadian institutionsDepartment of Environment and Conservation
FundersWellcome Trust
KeywordsBiologyBanksiaLongevityBotanyGenusProteaceae

Abstract

fetched live from OpenAlex

BACKGROUND AND AIMS: Serotiny is common in the genus Banksia, so any seed collection is likely to be comprised of seeds that were produced in many different years. This study aimed to determine the impact of cone age and degree of serotiny on longevity in ex situ storage. METHODS: Cones of identifiable age classes were collected from three species of Banksia. Seeds were extracted from cones and the degree of serotiny calculated. An estimate of initial viability (K(i)), the time for viability to fall by one probit (σ) and the relative longevity of seeds (p(50)) for each species and cone age class was determined using a comparative longevity test (50 °C, 63 % relative humidity). KEY RESULTS: The degree of serotiny ranged from moderate (7·9) for Banksia attenuata to strong (40·4) for B. hookeriana. Survival curves for all seed age classes within each species could be described by regressions with a common slope (1/σ), but with different values for K(i). The time taken for viability to fall by one probit (σ) could be described by a common value (29·1 d) for all three species. CONCLUSIONS: Differences in seed longevity between cone age classes and species was related to variation in initial viability (K(i)) rather than to differences in σ. While targeting the youngest mature seed cohort on a plant will maximize the viability of seeds collected, a wide range of age classes should be collected (but stored as separate cohorts if possible) for quality conservation/restoration seed collections where genetic diversity is important.

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 score0.915
Threshold uncertainty score0.135

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 head0.041
GPT teacher head0.282
Teacher spread0.242 · 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
Published2010
Admission routes1
Has abstractyes

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