Review of <i> Terrestrial Ecoregions of North America: A Conservation Assessment</i> by Taylor H. Ricketts and Eric Dinerstein
Bibliographic record
Abstract
Terrestrial Ecoregions of North America provides a comprehensive assessment of the status of biodiversity and conservation within the United States and Canada. Part of a global program conducted by the World Wildlife Fund, it is essentially a reference work offering baseline data for conservation planning and restoration. The book emphasises the precarious condition of many natural areas in North America, at the same time illustrating the great diversity that still exists in some areas and stressing the sense of urgency required to ensure the preservation of viable plant and animal populations in their natural habitats. It is not a textbook on conservation, however, but an evaluative report based on carefully described methodology and summary analysis that integrates an index of "biological distinctiveness" and an index of "conservation status" for 116 ecoregions. Ecoregions are defined as relatively large areas of land or water that contain geographically distinct assemblages of natural communities. As part of this assessment, ecoregion maps were compared with the ranges of over 20,000 North American species of native vascular plants, birds, butterflies, mammals, reptiles, amphibians, and terrestrial molluscs. Other procedures, equally comprehensive, considered information collected in other studies and assessments by expert committees.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".