Searching for the Lost Whaling Fleets of the Western Arctic
Bibliographic record
Abstract
In August 2015, a team of maritime archaeologists from ONMS/MHP and seabed mapping specialists from industry partners Edgetech and Hypack, went to the Arctic, with funding from the NOAA Office of Ocean Exploration, to search for 19th Century whaling shipwrecks in an area of the Chukchi Sea where more than 50 whaling ships were lost between 1850 and 1900. More than 30 of these lost whaling ships were from an event in September of 1871, when these ships were caught in the ice, abandoned, and more than 1200 people left on the ice with little hope of survival and rescue. Brad Barr, Co-PI and Mission Coordinator, will present background on why the ONMS Maritime Heritage Program went to the Arctic (the first Arctic field research conducted in the history of the ONMS), how the seabed mapping surveys were conducted, what was accomplished during this mission, and offer some “lessons learned” about the effective use of “platforms of opportunity” to further implementation of integrated ocean and coastal mapping. Additional background for the mission can be found on the Ocean Explorer webpage at: http://oceanexplorer.noaa.gov/explorations/15lostwhalingfleets/welcome.html. Presenter Bio Brad Barr received a B.S. from the University of Maine, an M.S. from the University of Massachusetts, and a Ph.D. from the University of Alaska. He is currently a Senior Policy Advisor in the NOAA Office of National Marine Sanctuaries, Affiliate Professor at the School of Marine Sciences and Ocean Engineering at the University of New Hampshire, and a Visiting Professor at the University Center of the Westfjords in Iceland. He is a member of the IUCN World Commission on Protected Areas, the International Committee on Marine Mammal Protected Areas/IUCN Marine Mammal Protected Areas Task Force. He has served on the Boards of Directors of the George Wright Society in the U.S., the Science and Management of Protected Areas Association (SAMPAA) in Canada and, currently, on the Board of Directors of the Coastal Zone Canada Association (CZCA). He also serves on the Editorial Board of the World Maritime University Journal of Maritime Affairs. He has published extensively on marine protected areas science and management, whaling and maritime heritage preservation, with a primary research focus on the identification and management of ocean wilderness.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".