Bibliographic record
Abstract
On 26 October 2015 the keel was laid for a remarkable new tanker at the Samsung Heavy Industries Shipyard, in Geoje, South Korea, the order having been placed by Sovcomflot, which operates the largest tanker fleet in Russia (Unicom Management Services (Cyprus) Ltd. 2015). The vessel was launched on 20 February 1916 and was named Shturman Albanov (Fig. 1). It is a shallow-draft icebreaking tanker of 42000 dwt (Unicom Management Services (Cyprus) Ltd. 2016) with a length of 249 m and the unusually large breadth for its tonnage, of 34 m, and a loaded draft of 9.5 m. Its ice-class is Arc7. Propelled by two 11 MW azipods (Fig. 2) (Sergey Frank, CEO of Sovcomflot, personal communication, July 2016) Shturman Albanov is capable of a speed of 14 knots. The azipods give it great manoeuverability and the capability of breaking ice up to 1.4 m thick when going ahead and 1.8 m thick when going astern. Registered in St. Petersburg and described as a shuttle tanker, it is designed specifically to haul oil from the Vorota Arktika (Gates of the Arctic) terminal near Mys Kamennyy, the terminal for Gazpromneft's Novoportovskoye field (Sergey Frank, CEO of Sovcmflot, personal communication, July 2016). The terminal is located on the east side of the Yamal Poluostrov, that is on the west shore of southern Obskaya Guba. This water-body is only about 10 m deep in places, which explains the need for a shallow-draft vessel, and for its unusually great breadth, in order to achieve maximum capacity. Another feature dictated by the shallow depths is that it is a bow-loading vessel. It will transport the oil year-round, west via Yuogorskiy Shar or Karskiye Vorota and across the Barents Sea to Murmansk where it will transfer its cargo to the storage tanker Umba. The delivery date for Shturman Albanov was 30 July (Staalesen 2016). In fact delivery and the naming ceremony took place on 20 July at Pusan, South Korea. The ship's captain is Vyacheslav Gafurov (Sergey Frank, CEO of Sovcomflot, personal communication, July 2016).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.013 |
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".