The value of timber inventory information for management planning
Bibliographic record
Abstract
Timber inventory data is the basis for many monetary transactions related to timber and timberland sale and (or) purchase as well as for development of timber management plans. The value of such data is well known and much appreciated for sale and (or) purchase of standing merchantable timber. Unfortunately, the value of timber inventory data for planning purposes is less well understood. We report on the results of a large simulation study that was undertaken to evaluate the utility and value of timber inventory data for timber management plan development for a typical timberland ownership in the southern United States. Our results indicate that timberland managers are likely producing management plans that do not maximize the profitability of their timberland holdings. Specifically, our results indicate it is likely that timber management organizations that develop timber management plans with stand level data that has a sampling error of 25% are experiencing expected losses in net present value in excess of 170 US$·ha–1 on a large proportion of the acreage found on typical timberland parcels in the southern United States.
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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 | 0.006 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".