Mapping on Top of the World: Ryder 2019 Expedition
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".