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Record W2772045938 · doi:10.1139/gen-2017-0173

Mitotic instability in triploid and tetraploid one-year-old eastern oyster, <i>Crassostrea virginica</i>, assessed by cytogenetic and flow cytometry techniques

2017· article· en· W2772045938 on OpenAlexvenueno aff
Joana Teixeira de Sousa, Standish K. Allen, Brittany M. Wolfe, Jessica Moss Small

Bibliographic record

VenueGenome · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicChromosomal and Genetic Variations
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyPloidyCrassostreaOysterChromosomeChromosome instabilityPolyploidKaryotypeCytogeneticsGeneticsZoologyFishery

Abstract

fetched live from OpenAlex

For commercial oyster aquaculture, triploidy has significant advantages. To produce triploids, the principal technology uses diploid × tetraploid crosses. The development of tetraploid brood stock for this purpose has been successful, but as more is understood about tetraploids, it seems clear that chromosome instability is a principal feature in oysters. This paper is a continuation of work to investigate chromosome instability in polyploid Crassostrea virginica. We established families between tetraploids-apparently stable (non-mosaic) and unstable (mosaic)-and normal reference diploids, creating triploid groups, as well as tetraploids between mosaic and non-mosaic tetraploids. Chromosome loss was about the same for triploid juveniles produced from either mosaic or non-mosaic tetraploids or from either male or female tetraploids. However, there was a statistically significant difference in chromosome loss in tetraploid juveniles produced from mosaic versus non-mosaic parents, with mosaics producing more unstable progeny. These results confirm that chromosome instability, as manifested in mosaic tetraploids, is of little concern for producing triploids, but it is clearly problematic for tetraploid breeding. Concordance between the results from cytogenetics and flow cytometry was also tested for the first time in oysters, by assessing the ploidy of individuals using both techniques. Results between the two were non-concordant.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.714
Threshold uncertainty score0.377

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 head0.023
GPT teacher head0.241
Teacher spread0.218 · 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 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

Citations18
Published2017
Admission routes1
Has abstractyes

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