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Record W4240938737 · doi:10.1121/2.0000977

The acoustics of the “Witches Valley”

2018· article· en· W4240938737 on OpenAlex
Gino Iannace, Umberto Berardi, Amelia Trematerra

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProceedings of meetings on acoustics · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Musicological Studies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsAcousticsComputer scienceGeologyPhysics

Abstract

fetched live from OpenAlex

According to the legend, witches were women with magical knowledge that with the use of herbs cured illnesses and performed spells. In 1639, the book “De Nuce Maga Beneventana” described how the place where the “witches” gathered was an area south of the city of Benevento in South Italy in a long and narrow gorge. This valley with high rock walls was called the “stretto di Barba”. According to the legend, under a walnut tree in the “stretto di Barba”, the Longobards were used to perform sacred rituals. To make the rituals more effective, the sounds were amplified by the narrow gorge with flat and parallel rock walls where the sound reflections generated echoing effects. The aim of this paper is to investigate the soundscape of the “stretto di Barba” and to investigate if it has the acoustic characteristics that create echoes and to confirm the legends about the Longobards’ rituals. In situ measurements were carried out. Numerical simulations were carried out using the acoustic software Odeon. The paper shows that if a place where the Longobards carried out their rituals really existed, then the “stretto di Barba” had all the proper acoustic characteristics to create multiple sound reflections and echoes.

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.

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.697
Threshold uncertainty score0.818

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.052
GPT teacher head0.224
Teacher spread0.173 · 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