A note on the slope correction and the estimation of the length of line features
Bibliographic record
Abstract
Length of line features, such as forest border, is among the ecologically interesting attributes estimated from forest inventories. In hilly terrain, observed line lengths must be corrected for slope. Contrary to the correction for standard area-related attributes (like volume per hectare), an overall correction of plot size is not sufficient, but the actual inclination of each individual line segment must be used for slope correction. This topic is discussed, and a mean correction factor is calculated as a function of terrain inclination assuming a uniform angular distribution of lines on the slope. Furthermore, the question is discussed whether the standard slope correction procedure for fixed-area circular field plots may possibly introduce a systematic error into the estimation of line length and also of standard area-related attributes. It is concluded that no relevant error is to be expected, neither with respect to point estimates nor to interval estimates. Data from the second Swiss National Forest Inventory serves for illustration.
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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 | 0.015 | 0.084 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".