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Record W2051139483 · doi:10.14704/nq.2014.12.4.772

Archaeoacoustic Investigation of a Prehistoric Cave Site: Frequency-Dependent Sound Amplification and Potential Relevance for Neurotheology

2014· article· en· W2051139483 on OpenAlexaff
J. Miguel Gaona, Nicolas Rouleau, Joey M. Caswell, Lucas W.E. Tessaro, Ryan C. Burke, D. Schumacher

Bibliographic record

VenueNeuroQuantology · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicArchaeology and Rock Art Studies
Canadian institutionsLaurentian University
Fundersnot available
KeywordsCavePrehistoryRelevance (law)Sound (geography)ArchaeologyComputer scienceGeologyGeographyOceanography

Abstract

fetched live from OpenAlex

An archaeoacoustic study was recently conducted within the important prehistoric cave system of El Castillo in northern Spain. With findings dating back at least 40800 years, archaeological studies of this cave have revealed the presence of prehistoric ritual activity associated with early shamanism. Simulated audio tones of varying frequencies were created and emitted from the location at which it is thought the shamans would conduct rituals within El Castillo, while the sound was simultaneously recorded from the likely location of potential observers or participants. Subsequent analysis identified a frequency-dependent amplification of recorded sound intensity for frequencies approaching the range of 100 Hz, with the greatest effect observed for 108 and 110 Hz. These results are markedly consistent with previous research of important or sacred sites which have shown significant sonic resonance features within this precise range of frequencies. Additional consideration is applied to the potential effects of 110 Hz physical stimuli on biological systems in the context of neurotheology and the associated biophysical analyses in order to demonstrate the potential importance of 110 Hz signals on religious experience and subjective states of consciousness.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.024
GPT teacher head0.287
Teacher spread0.263 · 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

Citations3
Published2014
Admission routes1
Has abstractyes

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