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Record W7047852906

Implementación del efecto Hass en técnicas de grabación para emular dimensiones y profundidad en recintos absorbentes

2007· dissertation· es· W7047852906 on OpenAlexaboutno aff

Bibliographic record

VenueDigital Library (University of San Buenaventura Colombia) · 2007
Typedissertation
Languagees
FieldPhysics and Astronomy
TopicAstronomy and Astrophysical Research
Canadian institutionsnot available
Fundersnot available
KeywordsTerm (time)Work (physics)Poison controlQuarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

A medida que se profundiza en las técnicas de la grabación y reproducción estéreo envolvente, generalmente muchos ingenieros de sonido manipulan los instrumentos mono en ubicaciones separadas, y después añaden múltiples procesos de reverberación estereofónicos, con el fin de crear espacio y profundidad en sus grabaciones. Sin embargo los resultados son pobres en la calidez, dimensiones, profundidad, y ubicación del sonido de los instrumentos musicales en las grabaciones multipista, realizadas en salas “sordas” con tiempos de reverberación bajos, pequeñas dimensiones y mucha absorción. Lo más utilizado hace algunos años para conseguir profundidad fue realizar grabaciones "naturalistas" de dos canales, aprovechándose de la acústica de la sala.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.002

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 head0.010
GPT teacher head0.263
Teacher spread0.254 · 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 designNot applicable
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
Published2007
Admission routes1
Has abstractyes

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