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Record W1880170908 · doi:10.1109/oceans.1997.634378

OASIS: ocean ambient sound system

2002· article· en· W1880170908 on OpenAlexaff
Len Zedel, Svein Østerhus, Richard Gordon

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsAmbient noise levelSound (geography)Wind speedAcousticsInstrumentation (computer programming)Sound qualityRemote sensingSoftwareGeologyEnvironmental scienceComputer scienceMarine engineeringEngineeringOceanographyPhysics

Abstract

fetched live from OpenAlex

The Ocean Ambient Sound Instrument System (OASIS) consists of a conventional RD Instruments ADCP modified to allow the recording of high quality, ambient sound from 1-75 kHz. In addition to the usual capabilities of an ADCP, this combination of acoustic instrumentation allows wind direction and speed to be inferred from a subsurface platform. The method of wind speed determination from ambient sound levels is explained identifying some of the limitations. The design of both the hardware and software required to make combined ADCP and ambient sound recordings is discussed, the methods used to preserve the large dynamic range characteristic of ambient sound. Observations made in the Norwegian Sea at OWS Mike are presented.

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)0.002
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 score0.057
Threshold uncertainty score0.190

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0570.035

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 head0.039
GPT teacher head0.226
Teacher spread0.187 · 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
Published2002
Admission routes1
Has abstractyes

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