Meteorological and sea surface water measurement data from Icebreaker Research Vessel ARAON for 2010-2019 Arctic research expeditions
Bibliographic record
Abstract
Despite of its economic and scientific significances with mineral resources, the Northern Sea Routes, and climate change, the Arctic Ocean has been a challenge for long-term continuous environmental observations. Since its inception in 2009, the ice-breaker research vessel ARAON has been conducting an annual expedition in the Arctic Ocean for the last 10 years from 2010. All the Arctic expeditions have been carried out mainly in August-September when the sea ice extent shrinks and the thickness becomes relatively thin around the Bering Sea, Chukchi Sea, Beaufort Sea, and high latitudes over the Russia, the US, and Canada. IBRV ARAON can conduct research activities through a variety of research equipment such as on-board meteorological data and surface temperature & salinity monitoring data of seawater. In this study, meteorological observation elements including solar radiation, air temperature, relative humidity, wind speed, and wind direction are presented. In addition, sea surface water temperature and salinity monitoring elements including water temperature, salinity, conductivity, and sound speed are presented.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
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".