D1.7 Recommendations from the joint scientific and operational workshop on implementation of shared European cruises
Bibliographic record
Abstract
The study of the Arctic Ocean has become a priority area of research and innovation in Europe and internationally during the past decades. This report reviews the input from an international virtual workshop during ASSW 2021 and a follow-up online survey initiated during ASSW 2022 about the bottlenecks and possible suggestions for how joint or shared European or international research cruises on research icebreakers (or polar research vessels) can be conducted to facilitate transnational Arctic research. While the challenges for typically national assets like research icebreakers are multiple and multi-level, the input from the workshop and survey describes possible ways to access research icebreakers and also identifies typical obstacles faced by scientists for such access.
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 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 | 0.067 | 0.071 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.008 | 0.011 |
| Research integrity | 0.024 | 0.012 |
| Insufficient payload (model declined to judge) | 0.058 | 0.036 |
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".