Kimberley Rainforests: A Focus on Biological Diversity
Bibliographic record
Abstract
For many years Kevin was a Principal Research Scientist with the Department of Environment and Conservation. His research has focused on the botany of the Kimberley and Top End, document-ing in particular the flora of remote rainforests and monsoon vine thickets. Kimberley rainforests total a mere 7000 hectares, less than 0.01% of the region, yet - incredibly - they contain around 25% of the region’s total plant species! Kevin began his fieldwork on the Dampier Peninsula back in 1977. Through the 1980s & 1990s, Kevin worked tirelessly with members of the Broome Botanical Society and Indigenous elders to document the local flora. This collaboration resulted in the 1996 landmark publication Broome and Beyond: plants and people of the Dampier Peninsula, gaining the team a CSIRO Medal for Re-search Achievement. Kevin is currently Adjunct Professor at UWA, as well as an Honorary Re-search Associate for the WA Herbarium & WA Museum.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".