MétaCan
Menu
Back to cohort
Record W333141781

Regional differences in bone collagen carbon- and nitrogen-isotope ratios of Pleistocene mammoths: Implications for paleoecology of the mammoth steppe

2010· article· en· W333141781 on OpenAlexaboutno aff
Darren R. Gröcke, Paul Szpak, Hendrik N. Poinar

Bibliographic record

VenueEGU General Assembly Conference Abstracts · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicPleistocene-Era Hominins and Archaeology
Canadian institutionsnot available
Fundersnot available
KeywordsBeringiaPleistoceneMammothSteppeGeologyRadiocarbon datingLast Glacial MaximumIsotopes of nitrogenQuaternaryPalynologyAridGlacial periodEcologyPhysical geographyArchaeologyPaleontologyGeographyStable isotope ratioBiology
DOInot available

Abstract

fetched live from OpenAlex

In this study, we present bone collagen carbon- and nitrogen-isotope values from a large set of Pleistocene woolly mammoths (Mammuthus primigenius) from Siberia, Alaska and Yukon (n=58). Overall, results for mammoth specimens from eastern Beringia (Alaska and Yukon) significantly differ, for both carbon- and nitrogen-isotope values, from those from western Beringia (northeastern Siberia). In agreement with palynological, entomological, and physiographic data from the same regions, these isotopic differences strongly imply that the ‘mammoth steppe’, the extensive ice-free region spanning northern Eurasia and northwestern North America, was ecologically variable along its east-west axis to a significant degree. Prior to the Last Glacial Maximum (LGM), the high-latitude portions of Siberia and the Russian Far East appear to have been colder and more arid than central Alaska and Yukon, which were ecologically more diverse. During the LGM itself, however, isotopic signatures of mammoths from eastern Beringia support the argument that this region also experienced an extremely cold and arid climate. In terms of overall temporal trend, Beringia thus went from a condition prior to the LGM of greater ecological variability in the east to one of uniformly cold and dry conditions during the LGM.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.263
Threshold uncertainty score0.750

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.037
GPT teacher head0.292
Teacher spread0.255 · 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 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

Citations0
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueEGU General Assembly Conference AbstractsSame topicPleistocene-Era Hominins and ArchaeologyFrench-language works237,207