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Record W7048935952

Mapping on Top of the World: Ryder 2019 Expedition

2020· article· en· W7048935952 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of New Hampshire Scholars Repository (University of New Hampshire at Manchester) · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsDingoSonarOil explorationArticular cartilage damage
DOInot available

Abstract

fetched live from OpenAlex

Ryder 2019 was an international, multidisciplinary scientific expedition to Northern Greenland aboard the Swedish Icebreaker Oden. The expedition’s primary goal was investigating the development and dynamics of the marine cryosphere and ocean conditions of the region that connects the Ryder Glacier to the southern Lincoln Sea, specifically in the Sherard Osborn Fjord and the northern Nares Strait. Secondary objectives include terrestrial research focusing on paleoclimatology and ecosystems. The land-sea connection of Ryder Glacier to the Nares Strait, is particularly of particular interest, as it’s one of the few places in the northern hemisphere where floating ice tongues exist and, due to the challenges of accessing this northern, ice-infested region, it’s never previously been explored by modern scientific means. To address our objectives, we conducted multidisciplinary scientific research over a broad range of disciplines including atmospheric chemistry and physics, biology, climatology, ecology, genomics, glaciology, oceanography, marine geology, geophysics and geochemistry. Presenter Bio Brian Calder is the Center's Associate Director. He has a Ph.D. in Electrical and Electronic Engineering, completing his thesis on Bayesian methods in Sidescan Sonar processing in 1997. Since then he has worked on a number of signal processing problems, including real-time grain size analysis, seismic processing, and wave-field modeling for shallow seismic applications. His research interests include methods for error modeling, propagation and visualization, and adaptive sonar backscatter modeling. His work has focused on developing methods for textural analysis of seafloor sonar data, as well as exploring innovative approaches to target detection and seafloor property extraction. Dr. Calder is currently focusing on statistically robust automated data cleaning approaches and tracing uncertainty in hydrographic data. Larry Mayer is a Professor and the Director of the Center for Coastal and Ocean Mapping at the University of New Hampshire. He graduated magna cum laude with an Honors degree in Geology from the University of Rhode Island in 1973 and received a Ph.D. from the Scripps Institution of Oceanography in Marine Geophysics in 1979. At Scripps, he worked with the Marine Physical Laboratory's Deep-Tow Geophysical package, applying this sophisticated acoustic sensor to problems of deep-sea mapping and the history of climate. After being selected as an astronaut candidate finalist for NASA's first class of mission specialists, Larry went on to a Post-Doc at the School of Oceanography at the University of Rhode Island where he worked on the early development of the Chirp Sonar and problems of deep-sea sediment transport and paleoceanography. In 1982, he became an Assistant Professor in the Dept. of Oceanography at Dalhousie University and in 1991 moved to the University of New Brunswick to take up the NSERC Industrial Research Chair in Ocean Mapping. In 2000 Larry became the founding director of the Center for Coastal and Ocean Mapping at the University of New Hampshire and the co-director of the NOAA/UNH Joint Hydrographic Center. Elizabeth Weidner is a jointly appointed PhD Student in Oceanography at the University of New Hampshire and Stockholm University. She graduated from the University of Washington in 2012 with a B.S. in Oceanography. Before coming to CCOM/JHC, she worked as a geophysicist for C&C Technologies. In May of 2018, she received her Master's in Earth Science: Ocean Mapping from the University of New Hampshire with a thesis titled: "A wideband acoustic method for direct assessment of bubble-mediated methane flux." Her current research is focused on the broadband acoustic discrimination and characterization of mixing phenomenon in the water column.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score0.183

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.020
GPT teacher head0.209
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 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

Citations0
Published2020
Admission routes1
Has abstractyes

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