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Record W3041337723 · doi:10.1038/s41597-020-0520-9

The International Bathymetric Chart of the Arctic Ocean Version 4.0

2020· article· en· W3041337723 on OpenAlexaff
Martin Jakobsson, Larry A. Mayer, Caroline Bringensparr, Carlos F. Castro, Rezwan Mohammad, Paul Johnson, Tomer Ketter, Daniela Accettella, David Amblàs, Lu An, Jan Erik Arndt, Miquel Canals, J. L. Casamor, Nolwenn Chauché, Bernard Coakley, Seth L. Danielson, Maurizio Demarte, Mary‐Lynn Dickson, Boris Dorschel, Julian A. Dowdeswell, Simon Dreutter, Alice Frémand, Dana Gallant, John K. Hall, Laura Hehemann, Hanne Hodnesdal, Jongkuk Hong, Roberta Ivaldi, Emily Kane, Ingo Klaucke, Diana Krawczyk, Yngve Kristoffersen, Boele R. Kuipers, Romain Millan, Giuseppe Masetti, Mathieu Morlighem, Riko Noormets, Megan M. Prescott, Michele Rebesco, Eric Rignot, Igor Semiletov, Alex J. Tate, Paola Travaglini, I. Velicogna, Pauline Weatherall, Wilhelm Weinrebe, J. K. Willis, Michael Wood, Yulia Zarayskaya, Tao Zhang, Mark Zimmermann, Karl Brix Zinglersen

Bibliographic record

VenueScientific Data · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological Studies and Exploration
Canadian institutionsCanadian Hydrographic ServiceGeological Survey of Canada
FundersStockholms UniversitetNatural Environment Research CouncilSight Research UKJet Propulsion LaboratoryNational Aeronautics and Space Administration
KeywordsBathymetric chartOceanographyBathymetryChartArcticThe arcticGeographyEnvironmental scienceGeologyMathematicsStatistics

Abstract

fetched live from OpenAlex

Bathymetry (seafloor depth), is a critical parameter providing the geospatial context for a multitude of marine scientific studies. Since 1997, the International Bathymetric Chart of the Arctic Ocean (IBCAO) has been the authoritative source of bathymetry for the Arctic Ocean. IBCAO has merged its efforts with the Nippon Foundation-GEBCO-Seabed 2030 Project, with the goal of mapping all of the oceans by 2030. Here we present the latest version (IBCAO Ver. 4.0), with more than twice the resolution (200 × 200 m versus 500 × 500 m) and with individual depth soundings constraining three times more area of the Arctic Ocean (∼19.8% versus 6.7%), than the previous IBCAO Ver. 3.0 released in 2012. Modern multibeam bathymetry comprises ∼14.3% in Ver. 4.0 compared to ∼5.4% in Ver. 3.0. Thus, the new IBCAO Ver. 4.0 has substantially more seafloor morphological information that offers new insights into a range of submarine features and processes; for example, the improved portrayal of Greenland fjords better serves predictive modelling of the fate of the Greenland Ice Sheet.

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)0.004
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.102
Threshold uncertainty score0.203

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0140.009

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 head0.071
GPT teacher head0.221
Teacher spread0.150 · 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
GenreDataset

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

Citations311
Published2020
Admission routes1
Has abstractyes

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