Bibliographic record
Abstract
In "Two Years Below the Horn," engineer Andrew Taylor vividly recounts his experiences and accomplishments during Operation Tabarin, a landmark British expedition to Antarctica to establish sovereignty and conduct science during the Second World War. When mental strain led the operation’s first commander to resign, Taylor—a military engineer with extensive prewar surveying experience—became the first and only Canadian to lead an Antarctic expedition. As commander of the operation, Taylor oversaw construction of the first permanent base on the Antarctic continent at Hope Bay. From there, he led four-man teams on two epic sledging journeys around James Ross Island,overcoming arduous conditions and correcting cartographic mistakes made by previous explorers. The editors’ detailed afterword draws on Taylor’s extensive personal papers to highlight Taylor’s achievements and document his significant contributions to polar science. This book will appeal to readers interested in the history of polar exploration, science, and sovereignty. It also sheds light on the little known contribution of a Canadian to a distant theatre of the Second World War. The wartime service of Major Taylor reveals important new details about a groundbreaking operation that laid the foundation for the British Antarctic Survey and marked a critical moment in the transition from the heroic to the modern scientific era in polar exploration.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.050 | 0.022 |
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".