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Record W2038128105 · doi:10.4043/12995-ms

Scotian Slope Mapping Project: The benefits of an integrated regional high-resolution multibeam survey

2001· article· en· W2038128105 on OpenAlexaboutno aff
Richard A. Pickrill, David J. W. Piper, James F. Collins, Marathon Oil, Art Kleiner, Lindsay Gee

Bibliographic record

VenueAll Days · 2001
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological formations and processes
Canadian institutionsnot available
Fundersnot available
KeywordsGeologyBathymetrySide-scan sonarSeabedGeological surveyBenthic zoneSonarGeophysical surveyOceanographyRemote sensingPaleontology

Abstract

fetched live from OpenAlex

Abstract A regional multibeam bathymetric and imagery survey of the Canadian Scotian Margin was performed by C & C Technologies, Inc. The survey was spearheaded by the Geological Survey of Canada (Atlantic), which acted as a partner with an industry group consisting of Marathon Canada, Norsk Hydro Canada, PanCanadian, and Murphy Oil. The survey is providing one component for use in hazard assessment within the lease block area of the central Scotian Slope, and forming an integral part of regional research carried out by the Geological Survey of Canada Atlantic (GSCA) funded by PERD and industry partners. The multibeam imagery is being used to derive a regional assessment of the character of seabed morphology, erosion, and the distribution of slope instabilities throughout the Scotian Slope. Spatial resolution is higher than in 3-D seismic data, especially on the mid to upper Slope, and the 17,000 km2 survey area provides regional coverage. Many of the large features (canyons and slope instabilities) on the Scotian Slope extend for many kilometers, and therefore their interpretation requires regional information. In particular, the multibeam imagery allows precise targeting of seabed features for subsequent higher resolution surveys of small critical areas and seabed sampling. Side scan sonar, sub-bottom profiling, and ROV surveys can provide fine detail of critical features. Precisely located samples can be used to obtain measurements of sediment properties, age dating of sediments, and benthic biota. A 30-day sampling cruise was performed by GSCA on the CCGS "Hudson", which acquired high-resolution seismic profiles and piston and box cores in targeted features. The targeted data will be used to ground truth the multibeam imagery and to assess geologic conditions and hazards of the Scotian Slope. The bathymetry data are being evaluated with new technology developed by the University of New Brunswick, Canada, which interactively integrates them into one common graphical environment and allows for precise identification of geologic correlations. Introduction Many exploration and production companies are showing interest in the Scotian Slope off eastern Canada. More than 3,000,000 ha. have been leased since 1999 (Fig. 1). In spring of 2000, C&C Technologies acquired more than 16,500 km2 of multibeam bathymetry (Fig. 2) and backscatter data from the central part of the Scotian Slope using an EM300 system. The survey covered 15 lease blocks and extended from about 700 m to 3000 m water depth. In addition, a separate survey by Clearwater Fine Foods Inc. and the Geological Survey of Canada acquired multibeam bathymetry from 700 m to 150 m water depth on the upper slope using an EM1002 system. The purpose of the survey was to provide the GSC(A) and industry partners with regional information on surficial hazards, including sediment slides, surface faulting, and pockmarks, and on the distribution of near surface sediments that influence benthic habitat. Following the acquisition of the multibeam data, the Geological Survey of Canada, with supplementary funding from the industry partners, carried out two 15-day confirmation cruises.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.318
Threshold uncertainty score0.639

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.067
GPT teacher head0.246
Teacher spread0.178 · 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

Citations11
Published2001
Admission routes1
Has abstractyes

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