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Record W2344660378 · doi:10.1038/nature17993

The genetic history of Ice Age Europe

2016· article· en· W2344660378 on OpenAlexaff
Qiaomei Fu, Cosimo Posth, Mateja Hajdinjak, Martin Petr, Swapan Mallick, Daniel Fernandes, Anja Furtwängler, Wolfgang Haak, Matthias Meyer, Alissa Mittnik, Birgit Nickel, Alexander Peltzer, Nadin Rohland, Viviane Slon, Sahra Talamo, Iosif Lazaridis, Mark Lipson, Iain Mathieson, Stephan Schiffels, Pontus Skoglund, А. П. Деревянко, NIKOLAI I. DROZDOV, V. S. Slavinsky, Alexander Alekseevich Tsybankov, Renata Grifoni Cremonesi, Francesco Mallegni, Bernard Gély, E. Vacca, Manuel R. González Morales, Lawrence Guy Straus, Christine Neugebauer-Maresch, Maria Teschler‐Nicola, Silviu Constantin, Oana Teodora Moldovan, Stefano Benazzi, Marco Peresani, Donato Coppola, Martina Lari, Stefano Ricci, Annamaria Ronchitelli, Frédérique Valentin, Corinne Thévenet, Kurt Wehrberger, Dan Grigorescu, Hélène Rougier, Isabelle Crèvecoeur, Damien Flas, Patrick Semal, Marcello A. Mannino, Christophe Cupillard, Hervé Bocherens, Nicholas J. Conard, Katerina Harvati, Vyacheslav Moiseyev, Dorothée G. Drucker, Jiřı́ Svoboda, Michael P. Richards, David Caramelli, Ron Pinhasi, Janet Kelso, Nick Patterson, Johannes Krause, Svante Pääbo, David Reich

Bibliographic record

VenueNature · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicForensic and Genetic Research
Canadian institutionsSimon Fraser University
FundersNational Institute of General Medical SciencesNational Institutes of HealthEuropean Social FundKoninklijk Belgisch Instituut voor NatuurwetenschappenRegione del VenetoRussian Science FoundationUnitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si InovariiUniversidad de CantabriaVetenskapsrådetMax-Planck-GesellschaftLeakey FoundationMinistero dell’Istruzione, dell’Università e della RicercaNational Natural Science Foundation of ChinaDeutsche ForschungsgemeinschaftIrish Research CouncilCalifornia State University, NorthridgeChinese Academy of SciencesWenner-Gren FoundationMinistero per i beni e le attività culturaliAustrian Science FundHoward Hughes Medical InstituteNational Science Foundation
KeywordsIce ageGeographyPhysical geographyEvolutionary biologyBiologyPaleontologyGlacial period

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.003
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.249
Teacher spread0.242 · 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 designObservational
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

Citations989
Published2016
Admission routes1
Has abstractno

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