Benthic macroinfaunal and dominant taxa samples collected from Northern Bering Sea to Chukchi Sea, 1970-2017
Bibliographic record
Abstract
As seasonal sea ice declines in much of the Arctic and reached record minima in 2012, oil and gas exploration are increasing, and additional ship traffic is also using Bering Strait, perhaps a portend of changes to come if the Northern Sea Route along the north coast of Russia becomes a practical ice-free route between Asia and Europe, reducing shipping costs significantly. The Northwest Passage through the Canadian Arctic has also become ice-free several times in recent summers, a significant change. All of the Arctic countries, including Russia, the United States, Canada, and Denmark (Greenland) are exploring the limits of their arctic continental shelves in order to advance claims under the Law of the Sea Treaty. Within this context of environmental and likely socio-economic changes, wildlife populations and human communities are adjusting to these shifts in seasonal sea ice coverage and climatic warming that has been much more obvious than at lower latitudes. Subsistence hunting patterns in the Arctic are changing, and it is also clear that many organisms, from plankton to top predators may be changing their migration and foraging patterns. Productivity is also forecast to change as sea ice declines and penetration of sunlight into open water increases. The Pacific Marine Arctic Regional Synthesis (*PacMARS*) is a research synthesis effort underwritten by the North Pacific Marine Research Institute to assemble by mid-year 2013 up-to-date written documentation that contributes to understanding the Pacific-influenced coastal shelf ecosystem of the Arctic Ocean. Our study's year range is from 1970-2017 and our study area extends from Saint Lawrence Island in the Bering Sea through Bering Strait into the Chukchi and Beaufort Seas. Our objective is to compile the best available knowledge from local communities, peer-reviewed social and natural sciences, as well as less readily available knowledge sources. The overall goal is to provide guidance for scientific research needs in the region, as well as to serve stakeholder needs for understanding this important ecosystem and its vulnerabilities. This dataset contains summary measurements of average benthic macroinfaunal taxa to the family level collected at each station for the identified cruise, with parameters of station, abundance in number per square meter (no/m2), wet weight biomass in grams wet weight per square meter (gww/m2), carbon dry weight biomass in grams carbon per square meter (gC/m2), and dominant benthic infauna based on the percentage for each measurement at a station. Note: this time-series dataset may be periodically updated as newer cruises are processed. For more information, see: https://pacmars.cbl.umces.edu/
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.004 |
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; both teacher heads agree on what is shown here.
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".