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Record W7134266172 · doi:10.5281/zenodo.18930288

Use it or lose it: A model-based assessment of the hypothesis that European Neanderthals relied on wildfires to create their campfires

2025· article· W7134266172 on OpenAlexaff
Andreu Arinyo-i-Prats, Dennis Sandgathe, Felix Riede, Mark Collard

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typearticle
Language
FieldSocial Sciences
TopicPleistocene-Era Hominins and Archaeology
Canadian institutionsSimon Fraser University
FundersEuropean Commission
KeywordsNeanderthalCounterintuitiveExploitMousterianHominidae

Abstract

fetched live from OpenAlex

Fire is a vital part of the hominin toolkit. There is debate, however, about Neanderthals’ pyrotechnical capabilities. They doubtlessly utilised fire, but multiple sites show a counterintuitive decrease in evidence for fire use during colder periods. This pattern has led some researchers to propose that some Neanderthals were unable to create fire from scratch and instead relied on wildfire. Here, we evaluate the plausibility of this hypothesis through formal modeling. Using numerical and analytical methods, we modeled the probability of a group of Neanderthals losing the skills necessary to exploit wildfire under different demographic and environmental conditions. Our results indicate that losing the ability to use wildfire was more likely than retaining the ability across most modeled scenarios due to cultural loss. This renders plausible that the reduction in fire evidence at many Neanderthal sites during colder periods is the result of Neanderthals having been reliant on wildfire.

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)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.112
GPT teacher head0.314
Teacher spread0.202 · 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 designSimulation or modeling
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
Published2025
Admission routes1
Has abstractyes

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Same venueZenodo (CERN European Organization for Nuclear Research)→Same topicPleistocene-Era Hominins and Archaeology→French-language works237,207→