Structures of bird communities in woodland remnants in central New South Wales, Australia
Bibliographic record
Abstract
The overall aim of this study was to investigate structures of bird communities in remnants of fragmented box/cypress pine woodlands in central New South Wales, Australia, to guide habitat rehabilitation. The aims of the study were to: (1) determine how bird densities and species richness varied with remnant category; (2) determine how ranked densities of bird species varied by feeding group with remnant category; and (3) provide information on structures of bird communities in box/cypress pine woodlands to guide restoration. Structures of bird communities varied with remnant category. Large remnants had the most species whereas medium-sized and small remnants in low condition had the fewest. Bird densities increased with decreasing remnant area although densities did not differ significantly between remnant categories. Ranked bird densities varied between remnant categories, with relatively even distributions in large remnants in high condition, and uneven distributions in small remnants in low condition. Densities of small insectivores were much lower in small, low-condition remnants than in large, high-condition remnants. Densities of generalists such as noisy miner and galah showed the reverse pattern. The structures of bird communities in large remnants in good condition provide a reference state for assessing recovery of bird communities.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".