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Record W4310437718 · doi:10.1038/s41586-022-05417-2

Reply to: When did mammoths go extinct?

2022· letter· en· W4310437718 on OpenAlexaff
Yucheng Wang, Ana Prohaska, Haoran Dong, Adriana Alberti, Inger Greve Alsos, David W. Beilman, Anders Anker Bjørk, Jialu Cao, Anna A. Cherezova, Éric Coissac, Bianca De Sanctis, France Denœud, Christoph Dockter, Richard Durbin, Mary E. Edwards, Neil R. Edwards, Julie Esdale, Grigory Fedorov, Antonio Fernàndez-Guerra, Duane Froese, Galina Gusarova, James Haile, Philip B. Holden, Kristian K. Kjeldsen, Kurt H. Kjær, Thorfinn Sand Korneliussen, Youri Lammers, Nicolaj K. Larsen, Ruairidh Macleod, Jan Mangerud, Hugh McColl, Marie Kristine Føreid Merkel, Daniel Money, Per Möller, David Nogués‐Bravo, Ludovic Orlando, Hannah L. Owens, Mikkel Winther Pedersen, Fernando Racimo, Carsten Rahbek, Jeffrey T. Rasic, Alexandra Rouillard, Anthony Ruter, Birgitte Skadhauge, John Inge Svendsen, Alexei Tikhonov, Lasse Vinner, Patrick Wincker, Yingchun Xing, Yubin Zhang, David J. Meltzer, Eske Willerslev

Bibliographic record

VenueNature · 2022
Typeletter
Languageen
FieldEarth and Planetary Sciences
TopicEvolution and Paleontology Studies
Canadian institutionsUniversity of Alberta
FundersU.S. Fish and Wildlife ServiceNovo NordiskH. Lundbeck A/SNational Science FoundationLundbeckfondenNational Natural Science Foundation of ChinaWellcome Trust
KeywordsGeographyEvolutionary biologyBiology

Abstract

fetched live from OpenAlex

Since the inception of ancient environmental DNA (eDNA) research, considerable attention has been paid to the depositional and diagenetic processes of DNA molecules in different sediments and settings 1 . Understanding those processes is critical to determine whether the recovered DNA is of the same age as the deposit in which it is found. It is therefore not unreasonable to ask, as Miller and Simpson have 2 in response to our recently published eDNA study of 50,000 years of Arctic ecosystem changes 3 , whether remains of long-dead megafauna might have contributed older DNA to younger deposits. They propose that this may account for our finding that mammoths persisted into the Holocene epoch in the continental Arctic.

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)0.006
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.109
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.028
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0080.004
Scholarly communication0.0060.005
Open science0.0020.003
Research integrity0.1090.063
Insufficient payload (model declined to judge)0.0130.013

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 head0.012
GPT teacher head0.230
Teacher spread0.218 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations4
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueNature→Same topicEvolution and Paleontology Studies→French-language works237,207→