Bibliographic record
Abstract
A stunning visual tour of the world's most spectacular caves and cave systems. Caves are found on every continent. The United States is home to the world's longest cave system, the Mammoth Cave in Kentucky, and to the world's most popular tourist cave, New Mexico's Carlsbad Caverns. Great Caves of the World takes readers to these and 25 other astonishing and challenging caves across the globe. Each entry includes lavish photographs and authoritative text describing the cave, its inhabitants, its environment, how and when it was discovered, access sites, and travel tips on how to get there.In addition to Carlsbad and Mammoth, featured caves include:Sterkfontein Cave in South Africa, the site of four-million-year-old hominid remains New Zealand's Waitomo Cave, dazzlingly illuminated by glow-worms The underground waterfalls of Gruta do Janelão, Brazil Looming glaciers of ice in Austria's limestone caves The cool Nullarbar Caves under the Australian desert Ethiopia's underground maze, the Sof Omar Cave The Caves of Mulu in Sarawak (Borneo), the world's largest Castleguard Cave in the Canadian Rockies. Geologists, expert cavers, spelunkers, climbers, adventure travelers, natural history enthusiasts and general readers will find this book fascinating.
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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 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.142 | 0.020 |
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".