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Supplementary material from "Ancient DNA of the Toronto Subway Deer Adds to the Extinction List of Ice Age Megafauna"

2025· other· en· W7084087397 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2025
Typeother
Languageen
FieldEngineering
TopicGeodetic Measurements and Engineering Structures
Canadian institutionsnot available
Fundersnot available
KeywordsMegafaunaOdocoileusExtinction (optical mineralogy)WoodlandPleistoceneAncient DNAPopulationBiodiversity

Abstract

fetched live from OpenAlex

The late Pleistocene was a time of global megafaunal extinctions that were particularly severe in North America. The continent lost many mammal taxa, but the validity of several remain ambiguous, including a high proportion of Cervidae taxa. Torontoceros hypogaeus is represented by a single specimen (ROMM75974) discovered in 1976 during excavation work for the Toronto subway in Canada. The species was described based on its unique antler morphology, but the variable nature of that trait and the species near absence in the fossil record leads to uncertainty concerning its systematic relationships. We used ancient DNA to clarify the taxonomic relationship and evolutionary history of T. hypogaeus. We performed mitochondrial and whole genome analyses with related cervids and showed that ROMM75974 has a close affinity, but relatively high divergence from the Odocoileus sister species. While some ambiguity remains, ROMM75974 could represent a distinct Odocoileus species to be included in the list of extinct North American taxa. This unique population was likely adapted to open landscape which was rapidly replaced with dense woodland in this region at the end of the Pleistocene, highlighting the role of climate change in the extinction of megafauna biodiversity at the end of the ice age.

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)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.975
Threshold uncertainty score0.330

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.7690.248

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 head0.011
GPT teacher head0.201
Teacher spread0.190 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2025
Admission routes1
Has abstractyes

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