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Record W2738907281 · doi:10.2298/gensr1701105c

Horse chestnut pollen quality

2017· article· en· W2738907281 on OpenAlexaff
Dušica Ćalić, Ljiljana Radojević

Bibliographic record

VenueGenetika · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Reproductive Biology
Canadian institutionsInstitute for Biological Sciences
FundersMinistarstvo Prosvete, Nauke i Tehnološkog Razvoja
KeywordsPollenGerminationBiologyBotanyPEG ratioPollen tubeHorticulturePolyethylene glycolStamenPollination

Abstract

fetched live from OpenAlex

Pollen quality of horse chestnut, expressed as pollen productivity, viability and germination was studied. Anthers of horse chestnut genotypes had pollen production from 3.66 to 5.06 x 103 pollen grains per anther, depending of genotype. Also, pollen of horse chestnut Ah1-Ah4 genotypes showed different viability (from 56 to 68%), after staining with fluorescein diacetate. Pollen germination of Ah1-Ah4 genotypes varied from 50-66% on basic medium. Inclusion of polyethylene glycol-PEG from 10%, 15% and 20% v/w increased pollen germination. The best results were achieved on medium with the largest PEG concentration. On these medium 76-91% pollen grains were germinated, depending of genotype. The best pollen quality, for all tested parameters, had genotype Ah2. Knowledge about morphology, production, viability, in vitro germination, tube growth as well as pollen: ovule ratio can be of great importance for future pollen biology studies.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.579
Threshold uncertainty score0.504

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 head0.036
GPT teacher head0.340
Teacher spread0.303 · 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

Citations7
Published2017
Admission routes1
Has abstractyes

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