Combining environmentally dependent and independent analyses of witness tree data in east-central Alabama
Bibliographic record
Abstract
We reconstructed pre-European settlement forest composition across 13 000 km 2 of east-central Alabama using 43 610 witness trees recorded in the original Public Land Surveys. First, we interpolated the witness tree data to estimate broad-scale vegetation patterns. Next, we conducted speciessite analysis on landforms, an approach that was dependent on underlying environmental variables yet better resolved fine-scale vegetation patterns. East-central Alabama was dominated by three community types: oakhickory across the Piedmont physiographic province and valleys of the Ridge and Valley province, pine blackjack oak on the Coastal Plain province and ridges of the Ridge and Valley province, and white oak mixed mesophytic in stream valleys and floodplains. Witness tree concentration (trees/km 2 ) was highly uniform across much of the study area. However, there was an unusually low concentration of witness trees in the southwestern corner of the study area, and an unusually high concentration in stream valleys. Another irregularity was the inability of surveyors to distinguish black oak and red oak. Overall, the interpolations provided an unbiased, yet broad-scale estimate of forest composition, while the specieslandform analysis greatly increased resolution of forest cover despite the subjectivity of defining environmental variables a priori.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 teacher head, 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".