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Record W2027250845 · doi:10.1121/1.4777941

Ferret and its applications

2005· article· en· W2027250845 on OpenAlex
Jacques Bédard

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2005
Typearticle
Languageen
FieldEngineering
TopicFire Detection and Safety Systems
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsMuzzleSoftware deploymentSupersonic speedComputer scienceMuzzle velocityAcousticsSoftwareProjectileAerospace engineeringAeronauticsGeologyComputer hardwareTelecommunicationsPhysicsEngineeringOperating systemMechanical engineering

Abstract

fetched live from OpenAlex

Ferret is an acoustic system that detects, recognizes and localizes the source and direction of small arms fire. The system comprises a small array of microphones and pressure sensors connected to a standard PC-104 computer that analyzes, displays, reports and logs the parameters of a recognized shot. The system operates by detecting and recognizing the ballistic shock wave created by the supersonic bullet, combined with the muzzle blast wave propagating from the weapon. The Canadian Land Force Test and Evaluation Unit evaluated a vehicle-mounted version of the system and recommended deployment of the system during peacekeeping missions. The system is the result of a collaborative effort between Defence R&D Canada and MacDonald Dettwiler and Associates. This presentation describes the hardware and software components of the system along with the current and future applications of the system.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.960
Threshold uncertainty score0.127

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.008
GPT teacher head0.219
Teacher spread0.211 · 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