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Record W3201808495 · doi:10.1101/2021.09.28.462146

Chromosome-scale genome assembly of the brown anole ( <i>Anolis sagrei</i> ), a model species for evolution and ecology

2021· preprint· en· W3201808495 on OpenAlexafffund
Anthony J. Geneva, Sungdae Park, Dan G. Bock, Pietro L. H. de Mello, Fatih Sarigol, Marc Tollis, Colin M. Donihue, R. Graham Reynolds, Nathalie Feiner, Ashley M. Rasys, James D. Lauderdale, Sergio G. Minchey, Aaron J. Alcala, Carlos R. Infante, Jason J. Kolbe, Dolph Schluter, Douglas B. Menke, Jonathan B. Losos

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2021
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaJohn Templeton FoundationNational Science Foundation
KeywordsAnolisBiologyGenomeEvolutionary biologyEcologyLizardGeneticsGene

Abstract

fetched live from OpenAlex

Abstract Rapid technological improvements are democratizing access to high quality, chromosome-scale genome assemblies. No longer the domain of only the most highly studied model organisms, now non-traditional and emerging model species can be genome-enabled using a combination of sequencing technologies and assembly software. Consequently, old ideas built on sparse sampling across the tree of life have recently been amended in the face of genomic data drawn from a growing number of high-quality reference genomes. Arguably the most valuable are those long-studied species for which much is already known about their biology; what many term emerging model species. Here, we report a new, highly complete chromosome-scale genome assembly for the brown anole, Anolis sagrei – a lizard species widely studied across a variety of disciplines and for which a high-quality reference genome was long overdue.

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)0.000
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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.198
Teacher spread0.187 · 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

Citations7
Published2021
Admission routes2
Has abstractyes

Explore more

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