Changes in the distribution of reports of the koala (Phascolarctos cinereus) after 16 years of local conservation initiatives at Gunnedah, north-west New South Wales, Australia
Bibliographic record
Abstract
In the early 1990s the koala became the mascot for a revegetation program to control salinity on agricultural land around Gunnedah in New South Wales, and a snapshot of the koala’s distribution in the shire was collected at that time, mainly via a mail survey. After the success of tree plantings in the 1990s, the koala population of the Liverpool Plains became a focus of increasing local conservation efforts, as well as research to explain koala population dynamics. This included a repeat mail survey conducted in 2006, which enabled the comparison of the reported distributions to be undertaken. These two citizen science surveys had different response rates but both produced extensive datasets. By 2006, koalas were reported from a wider extent than in 1990, particularly to the north and east of the town, and in more developed agricultural areas, but with highest densities in areas with more than 25% wooded vegetation. In 1990, koalas were reported mostly from locations that were surrounded by more than 40% wooded vegetation with the core of the distribution being on the basalt hills south of the town of Gunnedah. Koalas were also reported with increased relative frequency in the town, and this formed the core of the reported sightings at that time. There were still no reports from many of the vegetated hilly margins of the shire. The observed changes in the pattern of reporting reflects the actual distribution of koalas intersected with the likelihood of observation and the willingness of people to report koalas, and also identify the areas that may be under-sampled to determine the true habitat breath of koalas in the area.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".