The Use Of Taxonomic Diversity Indices In The Assessment OfPerturbed Community Recovery
Bibliographic record
Abstract
The spatial dynamics of ecological diversity are studied in two regions (Sudbury, Canada and Harjavalta, Finland) damaged by air pollution from copper and nickel smelting. Perturbation from pollution is assumed to be most intense near the source and to decrease with distance. Monitoring sites were therefore selected to traverse these pollution gradients. Using Rhyi's generalized entropy as a measure of diversity, a monotonic pattern of increasing diversity is discovered at the recovering Canadian sites but not at the Finnish sites. Quadratic entropy and a related information-theoretical measure of taxonomic diversity, taxonomic entropy, were calculated in the hope that these diversity indices, which incorporate taxonomic distances, would provide a better understanding of these unexpected results. Quadratic entropy has the additional advantage of making use of pairwise taxonomic distances between species in a highly intuitive manner. Taxonomic has a clear information-theoretical meaning and can be calculated in the same units of measurement as Rknyi's generalized entropy thereby facilitating the comparison of classical diversity to taxonomic diversity. Quadratic entropy was found to contribute little insight as to the state of ecological recovery relative to taxonomic entropy.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".