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Record W6888490737 · doi:10.18739/a23x83k85

Pacific Marine Arctic Regional Synthesis (PacMARS) benthic infauna, from Saint Lawrence Island, Alaska to the the East Siberian, Chukchi, and Beaufort Seas, Arctic Ocean, 1970-2012

2019· dataset· en· W6888490737 on OpenAlexaboutno aff

Bibliographic record

VenueUC Santa Barbara · 2019
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsArcticArctic ecologySea iceArctic dipole anomalyArctic ice packArctic sea ice declineMarine ecosystemContinental shelfContext (archaeology)

Abstract

fetched live from OpenAlex

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 area extends from Saint Lawrence Island in the Bering Sea through Bering Strait into the Chukchi and Beaufort Seas and 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, wet weight biomass (gww/m2), carbon dry weight biomass (gC/m2), number of taxa, Shannon-Wiener diversity and evenness indices, and number of grabs collected/station. For more information, see: https://pacmars.cbl.umces.edu/

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)0.003
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 score0.417
Threshold uncertainty score0.829

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.018
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0230.009

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 head0.019
GPT teacher head0.237
Teacher spread0.218 · 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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