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Record W6908458483 · doi:10.26022/ieda/330276

Processed bathymetry data (GeoTIFF images) acquired with a ship-mounted sonar system in 2019 on the continental slope of the Canadian Beaufort Sea

2021· other· en· W6908458483 on OpenAlexaboutno aff

Bibliographic record

VenueLDEO - Lamont-Doherty Earth Observatory, Columbia University · 2021
Typeother
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsBathymetrySonarHydrographyContinental shelfCruiseHydrographic surveyNautical mileSeabed

Abstract

fetched live from OpenAlex

This high-resolution gridded bathymetry data set was acquired with a ship-mounted Kongsberg EM2045 Multibeam sonar system in 2019. The file is in GeoTIFF image format, is projected in UTM coordinates (Zone 8N), and was processed using the open-source MB-System multibeam sonar processing software. The grid has 4-meter horizontal resolution. The survey mission was conducted during CCGS Sir Wilfrid Laurier IOS cruise 2019-090 in the Beaufort Sea (Cruise Chief Scientist - Humfrey Melling, Department of Fisheries and Oceans Canada; project PI - Scott Youngblut, Canadian Hydrographic Service). Data were acquired as part of a collaborative research project between MBARI, the Geological Survey of Canada, and Department of Fisheries and Oceans Canada.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.041
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.008
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0300.008

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 head0.022
GPT teacher head0.211
Teacher spread0.189 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2021
Admission routes1
Has abstractyes

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