Controlling coarse woody debris inventory quality: taper and relative size methods
Bibliographic record
Abstract
Accurately measuring the dimensions of coarse woody debris (CWD) is critical for ensuring the quality of CWD estimates and, hence, for accurately estimating forest ecosystem attributes (e.g., CWD carbon stocks). To improve the quality of CWD dimensional measurements, the distribution of taper (ratio of change in diameter and length) and relative size (RS; ratio of length and large-end diameter) of CWD pieces across the US were examined. Additionally, an outlier identification technique was developed by predicting the median and interquartile range of taper and RS as a function of large-end diameter, length, and decay class by major species group. The median CWD taper and RS across the US were 1.268 cm/m and 0.280 m/cm, respectively, with notable outliers. The taper and RS outlier identification protocol rapidly identified nearly 3% of study observations as outliers. Incorporation of CWD taper and RS outlier identification protocols into field data recorders may allow efficient control of measurement errors during field inventories.
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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 | 0.014 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".