"Birds of the World: A Checklist" by James F. Clements. 2000. [book review]
Bibliographic record
Abstract
conserve (migratory) shorebirds in the Yellow Sea region.At least the classical concepts might not work well, and RAMSAR agreements and other full-blown international political tool boxes are weak and soft; e.g., due to lack of enforcements and binding.Of interest is the progressive coastal ecoregion approach presented in Chapter 7, which allows one to characterise shorebird habitat with a variety of multidisciplinary habitat data.Much more of such work is needed in order to provide quantified results for shorebirds as well as their habitat.Although major countries like China, North and South Korea are currently not well known for their efforts to conserve shorebirds and their habitat, this publication will hopefully help to improve the current situation and force the governments eventually to take (coastal) environment issues seriously.The author can be congratulated for his tremendous effort providing the international community with such a splendid report on shorebird conservation and crucial baseline data.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.038 | 0.034 |
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".