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Record W2183809812 · doi:10.1139/cjz-2014-0068

First estimates of genome size in ribbon worms (phylum Nemertea) using flow cytometry and Feulgen image analysis densitometry

2014· article· en· W2183809812 on OpenAlexafffundvenue
Kelly Mulligan, Terra C. Hiebert, Nicholas W. Jeffery, T. Ryan Gregory

Bibliographic record

VenueCanadian Journal of Zoology · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine Biology and Ecology Research
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhylumBiologyGenome sizeGenomeFeulgen stainDensitometryEvolutionary biologyZoologyGeneticsDNAGene

Abstract

fetched live from OpenAlex

Ribbon worms (phylum Nemertea) are among several animal groups that have been overlooked in past studies of genome-size diversity. Here, we report genome-size estimates for eight species of nemerteans, including representatives of the major lineages in the phylum. Genome sizes in these species ranged more than fivefold, and there was some indication of a positive relationship with body size. Somatic endopolyploidy also appears to be common in these animals. Importantly, this study demonstrates that both of the most common methods of genome-size estimation (flow cytometry and Feulgen image analysis densitometry) can be used to assess genome size in ribbon worms, thereby facilitating additional efforts to investigate patterns of variability in nuclear DNA content in this phylum.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.226
Teacher spread0.215 · 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 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

Citations10
Published2014
Admission routes3
Has abstractyes

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