New methods for assessing Marbled Murrelet nesting habitat: Air photo interpretation and low-level aerial surveys
Bibliographic record
Abstract
This extension note summarizes the application of two new methods that were developed to assess the quality of forest habit that Marbled Murrelets (Brachyramphus marmoratus) use for nesting in British Columbia: air photo interpretation and low-level aerial surveys. Both methods use comparable sixlevel ranking systems that are based on the availability of forest attributes deemed important for nesting murrelets. The methods were developed and refined through preliminary work done in many varied coastal regions in British Columbia; they were designed to complement each other and be applicable to either small patches (1-2 ha) or to larger polygons used in mapping for forest management. Both methods were tested in comparisons with known murrelet nest sites and both are currently being applied by government and forest industry biologists. This note provides practitioners who are proposing to use one or both of these methods a concise guide to their suitability and limitations, and also provides links to relevant reports that offer greater detail on testing and applicability.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".