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Evolution of the nuclear genome of ferns and lycophytes

2008· book-chapter· en· W564485098 on OpenAlexaff
Takuya Nakazato, Michael S. Barker, Loren H. Rieseberg, Gerald J. Gastony

Bibliographic record

VenueCambridge University Press eBooks · 2008
Typebook-chapter
Languageen
FieldAgricultural and Biological Sciences
TopicFern and Epiphyte Biology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBiologyGenomeEvolutionary biologyPopulationAdaptation (eye)GeneticsIdentification (biology)GeneBotany

Abstract

fetched live from OpenAlex

Analyses of gene expression and function, genetic networks, population polymorphisms, and genome organization at the whole genome level have enabled research on previously intractable questions (reviewed in Wolfe and Li, 2003). Among plant lineages, genomic approaches have been most widely applied in the angiosperms, where significant resources have been developed. Angiosperm studies utilizing genome scale analyses have made several important advances, including the identification of an extensive history of genome duplications (Blanc et al., 2003; Schlueter et al., 2004; Cui et al., 2006), progress in understanding flower development and evolution (Doust et al., 2005; Whibley et al., 2006), characterization of the genetics underlying speciation and adaptation (Bradshaw and Schemske, 2003; Rieseberg et al., 2003; Lai et al., 2005; Eyre-Walker, 2006), the identification and mapping of recombination hot spots (Drouaud et al., 2006), and the discovery and role of microRNAs (Bartel and Bartel, 2003; Bartel, 2004). Genomic analyses will undoubtedly continue to provide tests of longstanding questions and offer novel perspectives in biology. For example, modern genomic analyses are capable of explaining the origin of the exceptionally high chromosome numbers of homosporous ferns and lycophytes, a result that will shed light on eukaryotic genome organization and evolution.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.952
Threshold uncertainty score0.223

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 head0.017
GPT teacher head0.153
Teacher spread0.136 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations55
Published2008
Admission routes1
Has abstractyes

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