The Status of the Panama Canal Watershed and Its Biodiversity at the Beginning of the 21st Century
Bibliographic record
Abstract
Panama is a small Central American country, but it operates a big canal and the world keeps an eye on developments there. Problems with the canal or ecological disasters in its watershed would attract a lot of attention. As Theodore Roosevelt planned, the Panama Canal is a major shipping corridor, transporting 37 ships a day and providing substantial income to the Panamanian government. Yet as Roosevelt could not have recognized—despite his interest in conservation—the canal sits in the center of one of the world's most biologically diverse areas (Myers et al. 2000): Southern Central America has more forest bird species than any other region in the world, except Amazonia and the northern and central andes, each of which is vastly larger than southern Central America (Stotz et al. 1996); and Panama has as many plant species per 10,000 km2 as any region in the world, more than Amazonia or the Malay Peninsula (Barthlott et al. 1996). Roosevelt may have suspected, though, that forests are crucial for protecting the water supply of the Panama Canal and for maintaining the plant and animal communities. Fortunately, the year 2000 still found extensive forests around the canal, protected largely thanks to military and shipping interests, but it also found the watershed adjacent to a large and expanding capital city. Maintaining the ecosystem integrity of the canal will pose a major challenge for conservation in the 21st century. Is urban and economic development compatible with a hydrologically functioning canal and conservation of an extremely diverse flora and fauna?
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".