MétaCan
Menu
Back to cohort
Record W2076848049 · doi:10.1093/molbev/msu074

Ancient Whole Genome Enrichment Using Baits Built from Modern DNA

2014· article· en· W2076848049 on OpenAlexaff
Jacob Enk, Alison Devault, Melanie Kuch, Yusuf E. Murgha, Jean-Marie Rouillard, Hendrik N. Poinar

Bibliographic record

VenueMolecular Biology and Evolution · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental DNA in Biodiversity Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBiologyGenomeDNADNA sequencingNuclear DNAGeneticsEvolutionary biologyAncient DNAComputational biologyMitochondrial DNAGene

Abstract

fetched live from OpenAlex

We report metrics from complete genome capture of nuclear DNA from extinct mammoths using biotinylated RNAs transcribed from an Asian elephant DNA extract. Enrichment of the nuclear genome ranged from 1.06- to 18.65-fold, to an apparent maximum threshold of ∼80% on-target. This projects an order of magnitude less costly complete genome sequencing from long-dead organisms, even when a reference genome is unavailable for bait design.

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)0.001
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 score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.009
GPT teacher head0.215
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 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

Citations140
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueMolecular Biology and EvolutionSame topicEnvironmental DNA in Biodiversity StudiesFrench-language works237,207