Surface sediment samples collected from US Coast Guard Healy, AK-North Pole-Dutch Harbor, Alaska, Healy2202-Synoptic Arctic Survey, 2022
Bibliographic record
Abstract
"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 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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.020 |
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".