POWER FROM ARCTIC WATERS
Bibliographic record
Abstract
An extended abstract of part of this paper was presented at the International Polar Year (IPY) Conference that took place in Oslo, Norway June 8-12, 2010. The present text is the complete version. It aims to confirm that ocean energies can be successfully tapped in polar environments and contribute to energy production and sustainable development of Nordic regions. Harnessing ocean waves has been proven possible and if such a scheme was decommissioned after some six years of operation the cause lies only with a storm of exceptional intensity. Lessons have been learned to lessen their impact. What may well remain an engineer’s dream is a scheme which may have a foundation in the OTEC ideas. Marine winds have not been tapped at these high latitudes in any significant manner, but may hold reasonable promise. Tidal energy has been used for centuries with both tidal current and rise and fall of tides put to work. They provided power for flour mills, saw mills, breweries etc. Their mills dotted several geographic areas regions of Europe from The Netherlands to Spain and from Wales to England, but also coastal areas of the United States and Canada and may be viewed as the forerunners of the power-generating tidal power stations. Utilizing the tidal processes has received considerable attention during the last few years as oil reserves, oil prices, climate changes cause increasing concern. China is considering building a plant and Korea (R.O.K.) has undertaken the construction of the largest ever tidal power station.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.062 | 0.014 |
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".