Interpreting patterns of population change in koalas from long-term datasets in Coffs Harbour on the north coast of New South Wales
Why this work is in the frame
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Bibliographic record
Abstract
We examined a long-term, repeat dataset for the koala population within Coffs Harbour Local Government Area. Analyses of these data have led to the conclusion that, following a perceived population decline in the 1980s, the koala population of Coffs Harbour has endured between 1990 and 2011 and showed no evidence of a precipitous decline during this period. Rather, the population change is best characterised as stable to slowly declining. This conclusion appears to contradict a common view of recent koala population declines on the north coast of New South Wales. There are four possible explanations for the population’s apparent stability: that conservation efforts and planning regulations have been effective; that surviving adults are persisting in existing home ranges in remnant habitat; that the broader Coffs Harbour population is operating as a ‘source and sink’ metapopulation; and/or that the standard survey methods employed are not sufficiently sensitive to detect small population changes. These findings do not mean there is no need for future conservation efforts aimed at koalas in Coffs Harbour; however, such efforts will need to better understand and account for a koala population that can be considered to be stable to slowly declining.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it