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Record W4400781403 · doi:10.46471/gigabyte.130

Chromosomal-level genome assembly and single-nucleotide polymorphism sites of black-faced spoonbill Platalea minor

2024· article· en· W4400781403 on OpenAlexaff
Jerome H. L. Hui, Ting‐Fung Chan, Leo Lai Chan, Siu Gin Cheung, Chi Chiu Cheang, James Kar‐Hei Fang, Juan Diego Gaitán‐Espitía, Stanley C. K. Lau, Yik‐Hei Sung, Chris K.C. Wong, Kevin Y. Yip, Yingying Wei, Wai Lok So, Wenyan Nong, Sean T.S. Law, Aiko Leong, Liz Rose-Jeffreys, Ho Yin Yip

Bibliographic record

VenueGigabyte · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsHealth PEI
FundersChinese University of Hong Kong
KeywordsBiologyGenomeSequence assemblyMinor allele frequencyGeneticsEndangered speciesEvolutionary biologyGeneSingle-nucleotide polymorphismHabitatEcologyGenotype

Abstract

fetched live from OpenAlex

Platalea minor, or black-faced spoonbill (Threskiornithidae), is a wading bird confined to coastal areas in East Asia. Due to habitat destruction, it was classified as globally endangered by the International Union for Conservation of Nature. However, the lack of genomic resources for this species hinders the understanding of its biology and diversity, and the development of conservation measures. Here, we report the first chromosomal-level genome assembly of P. minor using a combination of PacBio SMRT and Omni-C scaffolding technologies. The assembled genome (1.24 Gb) contains 95.33% of the sequences anchored to 31 pseudomolecules. The genome assembly has high sequence continuity with scaffold length N50 = 53 Mb. We predicted 18,780 protein-coding genes and measured high BUSCO score completeness (97.3%). Finally, we revealed 6,155,417 bi-allelic single nucleotide polymorphisms, accounting for ∼5% of the genome. This resource offers new opportunities for studying the black-faced spoonbill and developing conservation measures for this species.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score0.809

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 head0.023
GPT teacher head0.229
Teacher spread0.206 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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