Biological survey and setting priorities for flora conservation in Western Australia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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) | 0.002 | 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 it