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Record W2102938566

Comparison of measured and modelled transmission loss in emerald basin

2008· article· en· W2102938566 on OpenAlexaffvenue
B.H. Maranda, Nicole E. Collison

Bibliographic record

VenueCanadian acoustics · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsProjectorTransmission lossAcousticsTelemetryGeologySound pressureSea trialTransmission (telecommunications)EmeraldDuct (anatomy)Remote sensingPhysicsElectrical engineeringTelecommunicationsOpticsEngineeringMineralogyOceanography
DOInot available

Abstract

fetched live from OpenAlex

The measured and modeled transmission loss (TL) in the Emerald Basin was investigated. An acoustic projector was towed at 50-m depth by the research ship CFAV Quest. The transmitted signal consisted of 11 continuous-wave (CW) tones spaced 100 Hz apart from 1010 to 2010 Hz. The sonobuoy receivers were set for a depth of either 60 m or 120 m, and the received acoustic signals were relayed to the ship over a radio-frequency (RF) telemetry link. A sound-speed profile from the day of the experiment shows a pronounced duct with an axis close to the source depth. The data collected during the sea trial were later processed to yield estimates of the transmission loss through the equation TL = SL-SPL, where SL is the projector source level and SPL was the sound pressure level at the receiver. The curves at the different frequencies cluster quite closely together, but the TL was markedly less for the 60-m receiver than for the 120-m receiver. It was observed that the TL curves for the 60-m receiver display the low loss.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.058
GPT teacher head0.270
Teacher spread0.213 · 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

Citations0
Published2008
Admission routes2
Has abstractyes

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