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Record W7098433137

Canadian Acoustics I Acoustique Canadienne 18(2)25-31 (1990) THREE DIMENSIONAL ACTIVE NOISE CANCELLATION USING SPHERICAL ARRAYS OF CARDIOID SOURCES

2016· article· en· W7098433137 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicBerberine and alkaloids research
Canadian institutionsnot available
Fundersnot available
KeywordsLoudspeakerArchitectural acousticsNoise (video)Room acousticsActive noise control
DOInot available

Abstract

fetched live from OpenAlex

Computer modelling is used to design a two element loudspeaker sys tem ('tripole') capable of generating an accurate cardioid radiation pattern for frequencies below 500 Hz. The model is used to assess the effectiveness of various spherical arrays of such tripoles at cancelling a spherical sound field. One cancelling tripole array is built and found to behave in accordance with the model predictions. SOMMAIRE La modélisation par ordinateur est employe dans le concept d 'un systeme (tripoles) a deux elements capabale de generer un profil car-dioide precis de radiation pour des frequences inférieures a 500 Hz. Le modele est employe pour evaluer l'efficacite des étalagés spheriques de telles tripoles afin de reduire le champs spheriques de sonorité. Un étalagé tripoles d'annulation est construit et il est trouve que son comportement suit le modele de prediction.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.255
Threshold uncertainty score0.507

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0630.015

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 head0.030
GPT teacher head0.281
Teacher spread0.251 · 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 designBench or experimental
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
Published2016
Admission routes1
Has abstractyes

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Same topicBerberine and alkaloids researchFrench-language works237,207