Bibliographic record
Abstract
If you dream of adventure in frozen landscapes, this book may be for you. However, this coffee table book is not for everyone. It is written in French, German, and English, but not in the usual manner of books in 3 languages. There is parallel text in only a few places. Those who don't read all 3 languages will have to content themselves with looking at the photos in many of the chapters. The entire book is well-illustrated, although most of the images are of horizontal white landscapes with and without camps or warmly clad people. There are also some photos of polar bears, gear, and settlements. The first section: “Annäherung an die Polargebiete” (Approach to Polar Regions) is written mostly by invited authors. This section is divided into 4 parts. The first part, “Ice,” includes chapters on “The Arctic and the International Polar Year” and “Inuit Sculpture” (in French), as well as “Polar Bears Don't Eat Penguins … Geographical Notes about the Arctic” (in German), and “Dog Sledging in Greenland” (in English). The other 3 parts are comprised of a short philosophical section, with the title “Flow,” and 2 practical parts of one chapter each. The first covers the use of large kites for propulsion (in German); the second gives advice for traveling in polar bear country (in English). The second and third sections of the book recount 2 expeditions by the author, Patrick Peters, a polar explorer from Luxembourg. The first trip was to the North Pole in 2003, the other across Greenland in 2008. Each section contains some assorted information, some tips for polar travel, and an account of the expedition. The expedition sections also contain detailed gear lists. Ice-Flow is not so much a unified book as a compilation of random information about the Arctic and polar travel in large format with photographs. The chapters on kites and polar bears might be useful for anyone planning a polar trip. Those who must have everything published about Arctic exploration or who want to impress their friends with their erudition will want to buy this book.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.314 | 0.206 |
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".