Bibliographic record
Abstract
Hidden high in the Sierra de Guatemala mountain range of northeastern Mexico in the state of Tamaulipas is the northernmost tropical cloud forest of the Western Hemisphere. Within its humid oak-sweetgum woodlands, tropical and temperate species of plants and animals mingle in rare diversity, creating a mecca for birders and other naturalists. Fred and Marie Webster first visited Rancho del Cielo, cloud forest home of Canadian immigrant Frank Harrison, in 1964, drawn by the opportunity to see such exotic birds as tinamous, trogons, motmots, and woodcreepers only 500 miles from their Austin, Texas, home. In this book, they recount their many adventures as researchers and tour leaders from their base at Rancho del Cielo, interweaving their reminiscences with a history of the region and of the struggle by friends from both sides of the border to have some 360,000 acres of the mountain declared an area protected from exploitation—El Cielo Biosphere Reserve. Their firsthand reporting, enlivened with vivid tales of the people, land, and birds of El Cielo, adds an engagingly personal chapter to the story of conservation in Mexico.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.056 | 0.007 |
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".