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Record W6963633683 · doi:10.18739/a25q4rn9f

Surface sediment samples collected from US Coast Guard Healy, AK-North Pole-Dutch Harbor, Alaska, Healy2202-Synoptic Arctic Survey, 2022

2024· dataset· en· W6963633683 on OpenAlexaboutno aff

Bibliographic record

VenueCalifornia Digital Library · 2024
Typedataset
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsArcticBiogeochemical cycleEcosystemArctic ecologySea iceCoast guardClimate changeMarine ecosystem

Abstract

fetched live from OpenAlex

"The Central Arctic Ocean remains profoundly understudied, particularly with respect to carbon cycling, ecosystem alteration, and associated changes in atmospheric, ice and ocean physics that drive those biological and biogeochemical systems. The region is expected to experience continued marked changes over the coming decades, driven by ongoing climate warming. Yet, because of relatively limited understanding of fundamental characteristics and processes in the region, predicting these changes and their Pan-Arctic linkages remains difficult. The Synoptic Arctic Survey (SAS) is organized around three major research areas: (1) physical drivers of importance to the ecosystem and carbon cycle; (2) the ecosystem response and (3) the carbon cycle. The overarching questions are: “What is the present state, and what are the major ongoing transformations of the Arctic marine system?” The overall objective of this expedition was to quantify the present states of the physical, biological, and biogeochemical systems of the Pacific Arctic (here defined as the Chukchi Sea, Beaufort shelf/slope, Chukchi Borderlands) and Canadian Basin (i.e., the Makarov and Canada basins) during summer 2022. A key goal is to document temporal changes where possible by comparison with historical data and to quantify linkages among adjacent shelves, slopes, and deep basins on a Pan-Arctic scale. These objectives are part of the International Synoptic Arctic Survey (SAS; 2021-2022) that seeks Pan-Arctic understanding of core ocean variables on a quasi-synoptic, spatially distributed basis using coordinated, international efforts. The findings of this expedition, a US contribution to the SAS, will be a foundation and legacy for future, quasi-decadal assessments of rapid and evolving Arctic Ocean system change." - Cruise Report USCGC Healy HLY2202/AWS2022 [Prepared by Carin Ashjian (cashjian@whoi.edu) and the HLY2202 Science Team]

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.350
Threshold uncertainty score0.695

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.012
GPT teacher head0.194
Teacher spread0.182 · 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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

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