A new method for characterizing point patterns in plant ecology
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract. This paper describes new methods for the detection of the characteristics of spatial point patterns, based on counting plants in the circumcircles of triangles defined by triplets of the points themselves. In addition to counting points in the circumcircle, a further refinement is to count also the points in a ring around the circumcircle of the same area. This approach can be applied in a univariate form, with one species or one kind of plant, to detect and evaluate the best‐defined patches of plants and gaps. In the bivariate form, the method can be used to investigate the spatial characteristics of the relationship between different kinds of plants. These methods are illustrated by application to several data sets. In particular, the method is shown to be useful in describing the spatial relationship between seedlings and trees, both when the seedlings are on the forest floor beneath the canopy trees and when the seedlings represent post‐fire regeneration.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it