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Record W2583607119 · doi:10.1080/19420889.2017.1283080

The plastid genomes of nonphotosynthetic algae are not so small after all

2017· letter· en· W2583607119 on OpenAlexaff
Francisco Figueroa‐Martinez, Aurora M. Nedelcu, Adrián Reyes‐Prieto, David Roy Smith

Bibliographic record

VenueCommunicative & Integrative Biology · 2017
Typeletter
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Parasitism and Resistance
Canadian institutionsWestern UniversityCanadian Institute for Advanced ResearchUniversity of New Brunswick
Fundersnot available
KeywordsPlastidBiologyGenomeChloroplast DNAAlgaePhotosynthesisEvolutionary biologyChloroplastGreen algaeBotanyGeneGenetics

Abstract

fetched live from OpenAlex

The thing about plastid genomes in nonphotosynthetic plants and algae is that they are usually very small and highly compact. This is not surprising: a heterotrophic existence means that genes for photosynthesis can be easily discarded. But the loss of photosynthesis cannot explain why the plastomes of heterotrophs are so often depauperate in noncoding DNA. If plastid genomes from photosynthetic taxa can span the gamut of compactness, why can't those of nonphotosynthetic species? Well, recently we showed that they can. The free-living, heterotrophic green alga Polytoma uvella has a plastid genome boasting more than 165 kilobases of noncoding DNA, making it the most bloated plastome yet found in a heterotroph. In this addendum to the primary study, we elaborate on why the P. uvella plastome is so inflated, discussing the potential impact of a free-living vs. parasitic lifestyle on plastid genome expansion in nonphotosynthetic lineages.

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)0.002
metaresearch head score (Gemma)0.011
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: none
Teacher disagreement score0.015
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.003
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0150.018
Insufficient payload (model declined to judge)0.0040.007

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 head0.265
Teacher spread0.224 · 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

Citations6
Published2017
Admission routes1
Has abstractyes

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