Bibliographic record
Abstract
Russia's Icebreaker Capabilities -Arctic OceanArktika class icebreakers are the bulk of the Russian nuclear icebreaker fleet, used primarily to aid shipping along the Northern Sea Route.Of the seven nuclear icebreakers, one is a containership with an ice-breaking bow, and two, the "Taymyr" and the "Vaygach" have been built for shallow waters in rivers transporting lumber, ore and other cargo.Approximately 2,000 people work aboard the icebreakers, which are based at the Atomlot harbour in the Murmansk Fjord.Arktika class icebreakers have a double hull and can operate in ice in 2.5 meters (8.2 ft) thick at speeds of up to 10 knots.In ice-free waters, the maximum speed of these ships is as much as 21 knots.There is water ballast between the inner and outer hulls which can be shifted to aid icebreaking operations.Icebreaking is also assisted by an air bubbling system which delivers air from jets below the surface.The ships have two reactors, three propellers totaling 75,000 hp, and can operate for approximately 7 months at sea and 4 years between refuelling.The crew normally includes 130-200 personnel.The 50 Let Pobedy, built in 2007, is the world's largest nuclear icebreaker, at 159 meters in length.It also carries two Ka-32 helicopters.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".