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Record W4245230631 · doi:10.1121/2.0000962

Seabed properties at the 150 m isobath as observed during the 2016-2017 Canada Basin Acoustic Propagation Experiment

2018· article· en· W4245230631 on OpenAlexaboutno aff
Jason D. Sagers, Megan S. Ballard

Bibliographic record

VenueProceedings of meetings on acoustics · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsnot available
Fundersnot available
KeywordsLayeringGeologySeabedCoringSeafloor spreadingSedimentOceanographySound (geography)Waves and shallow waterSound propagationAcousticsGeomorphologyDrilling

Abstract

fetched live from OpenAlex

Seabed layering and sediment properties impact sound propagation in ocean waveguides, particularly in environments where sound propagation paths repeatedly interact with the seafloor. As part of the 2016–2017 Canada Basin Acoustic Propagation Experiment (CANAPE), experiments were designed to investigate seabed layering and sediment properties on the Chukchi Shelf. First, the shallow water experimental region was surveyed with a subbottom profiler to provide information about the overall sediment layering. Second, ship-radiated noise from a research vessel sailing specifically designed tracks was received on the Persistent Acoustic Observation System (PECOS). These recordings provide an opportunity for short- to mid-range geoacoustic inversion for sediment properties. Third, in-situ acoustic sound speed measurements were made with the Acoustic Coring System (ACS) while two to five meter long core samples were simultaneously collected. This talk presents initial findings of the seabed layering and sediment properties from these three experiments.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.181
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.031
GPT teacher head0.230
Teacher spread0.199 · 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 teacher head, 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

Citations3
Published2018
Admission routes1
Has abstractyes

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