Bibliographic record
Abstract
Saara Matala’s article “Finnish–Soviet nuclear icebreakers” (Physics Today, September 2020, page 38) gives an account of how the small Western country of Finland managed to maintain its neutrality and start a commercial collaboration with the Soviet Union based on icebreakers. What struck me most in the article was figure 1, which depicts the routes around the Arctic Ocean: the Northern Sea Route along Siberia and the Northwest Passage along Canada. Almost every article I have read regarding the early and accelerating melting of the Arctic ice stresses the importance of the albedo difference between intact ice and free ocean water (see, for example, “The thinning of Arctic sea ice,” by Ron Kwok and Norbert Untersteiner, Physics Today, April 2011, page 36).When I read that Finland’s “five Moskva-class polar icebreakers” were “designed to cut through multiyear Arctic sea ice,” my mind linked icebreakers with the premature Arctic melt. Icebreakers keep the routes in figure 1 open most of the year—if not year-round—for commercial shipping. Thus they initiate or at least aggravate the melting of multiyear sea ice: Breaking the ice allows the open waters to warm with respect to the surrounding ice due to the albedo difference, with probably a very small addition from the heat generated by the ships themselves. I therefore find it hard to believe that a Physics Today news story (September 2017, page 24), for example, advocates the use of new icebreakers “to gauge global effects of the polar region’s diminishing ice cover.” I have to wonder if the models regarding Arctic warming have taken the effect of icebreakers into consideration. Section:ChooseTop of page <<CITING ARTICLES© 2021 American Institute of Physics.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 | 0.000 |
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 teacher head, 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".