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Record W984744195

Extraction of seabed geomorphologic features of Svalbard fjords using high-resolution side scan sonar

2008· article· en· W984744195 on OpenAlexaff
Jarosław Tęgowski, Jerzy Giżejewski, A. Zieliński

Bibliographic record

VenueHydroacoustics · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsFjordGeologyGlacierArcticSeafloor spreadingOceanographyTidewater glacier cycleBathymetrySediment transportSide-scan sonarSonarGeomorphologySedimentIce calving
DOInot available

Abstract

fetched live from OpenAlex

This paper presents results of a study on the relationship between features of side scan sonar acoustic imagery of zones with active bedforms and geomorphologic seafloor characteristics. Acoustic measurements were conducted in Hornsund, a Svalbard fjord representing a periglacial environment with great intensity of morphodynamic processes and rapidly progressing changes of tidewater glaciers. Due to the intensity of these processes, Arctic fjords are the most promising areas to study the effects of climate change on the ecosystem. Acoustic identification of sedimentary structures and morphological forms created by currents and iceberg transport of glacier sediment away from the ice margin was performed. The spectral and fractal features of the recorded signals were analysed. The proposed analysis scheme allows identification of the morphodynamic active zones in the changing Arctic fjord environments. Measurements of acoustical features of seafloor surface were made during the 2006 Arctic cruise of r/v Oceania.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.049
GPT teacher head0.268
Teacher spread0.219 · 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

Citations1
Published2008
Admission routes1
Has abstractyes

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