Biological survey and setting priorities for flora conservation in Western Australia
Bibliographic record
Abstract
Biological survey has been an integral component of conservation planning in Western Australia for >30 years, providing baseline data for reserve selection and the management of biodiversity at the genetic, species and community levels. Flora surveys are particularly important, given the diverse and poorly documented nature of the state’s vascular flora. Surveys have been conducted at the following four scales: regional, subregional, local and individual species. At all scales, flora surveys have provided detail on individual taxon distribution, have identified previously unknown or unrecognised taxa, have located presumed extinct taxa and have substantially contributed to information on the distribution of threatened flora. Regional-scale surveys normally involve multidisciplinary teams studying a broad selection of the biota. These combined plot-based data are used to develop a ‘classify-then-model’ approach to assessment of comprehensiveness, adequacy and representativeness of the regional conservation reserve system. These regional models describe the broad-scale patterning of common taxa but their utility in reflecting patterns in naturally rare or highly restricted taxa is uncertain. Results from recent surveys show poor correlations between floristic patterning and other components of the biota.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".