Mistletoe flora (Loranthaceae and Santalaceae) of the Kimberley, a tropical region in Western Australia, with particular reference to fire
Bibliographic record
Abstract
The mistletoe flora of the tropical Kimberley region of Western Australia was studied over a 30-year period, with a particular emphasis on distributions, use of hosts and effects of fire. The results were compared with those of a similar study undertaken in the Pilbara, a more arid tropical region in the same State. The flora consisted of one genus with three species in the Santalaceae and five genera with 22 species (one with two varieties) in the Loranthaceae. Amyema was the largest genus in both regions. Four species are regarded as Kimberley endemics but two of them may also occur in the Northern Territory. Most species occurred in three or more of five Kimberley bioregions. However, six species were recorded only from the North Kimberley where they were all rare. Host records included 165 species from 33 families. Fabaceae (particularly Acacia) and Myrtaceae (particularly Eucalyptus and Corymbia) were the most important. The perfect dichotomy between species using fabaceous and myrtaceous hosts in the Pilbara was strong but imperfect in the Kimberley. Fire responses of two species were not observed. Two (perhaps three) taxa were able to resprout, whereas the remaining taxa were killed if scorched. Most species occurred, at least occasionally, in relatively fire-safe refugia. Nevertheless, fire is eroding distributions of many species and may be threatening some, particularly the rare North Kimberley species.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 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".