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Record W2126767783 · doi:10.1073/pnas.1421374112

Genomic perspectives on the birth and spread of plastids

2015· article· en· W2126767783 on OpenAlexafffund
John M. Archibald

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtist diversity and phylogeny
Canadian institutionsDalhousie UniversityCanadian Institute for Advanced Research
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsEndosymbiosisPlastidBiologyHorizontal gene transferContext (archaeology)AlgaeEvolutionary biologyTree of life (biology)Green algaeGeneBotanyGenomePhylogeneticsGeneticsChloroplastPaleontology

Abstract

fetched live from OpenAlex

The endosymbiotic origin of plastids from cyanobacteria was a landmark event in the history of eukaryotic life. Subsequent to the evolution of primary plastids, photosynthesis spread from red and green algae to unrelated eukaryotes by secondary and tertiary endosymbiosis. Although the movement of cyanobacterial genes from endosymbiont to host is well studied, less is known about the migration of eukaryotic genes from one nucleus to the other in the context of serial endosymbiosis. Here I explore the magnitude and potential impact of nucleus-to-nucleus endosymbiotic gene transfer in the evolution of complex algae, and the extent to which such transfers compromise our ability to infer the deep structure of the eukaryotic tree of life. In addition to endosymbiotic gene transfer, horizontal gene transfer events occurring before, during, and after endosymbioses further confound our efforts to reconstruct the ancient mergers that forged multiple lines of photosynthetic microbial eukaryotes.

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)0.001
metaresearch head score (Gemma)0.002
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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.003
Scholarly communication0.0030.004
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.039
GPT teacher head0.271
Teacher spread0.232 · 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

Citations164
Published2015
Admission routes2
Has abstractyes

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