OpenJUMP HoRAE—A free GIS and toolbox for home‐range analysis
Bibliographic record
Abstract
Abstract Over the past 20 years a set of methods for home‐range estimation and analysis of animal observation data have been developed. Whereas comparisons among the estimation methods and different estimation software are available, only the adehabitat analysis toolbox for R is under a free and open‐source software license and includes established and new home‐range estimation approaches, such as Kernel Density Estimation, Brownian Bridges, and Local Convex Hulls. However, R and adehabitat are command line based, which some may perceive as not very user‐friendly, and provide only a limited set of functions for the analysis of home ranges with environmental geospatial data (e.g., land cover and elevation data). This article presents a free and open‐source home‐range analysis toolbox that focuses on the evaluation of global positioning system collar data, and integrates with a desktop geographic information system to allow data analysis beyond the creation of home ranges. The software is distributed under a free and open‐source license, so research can also benefit from the toolbox because implemented algorithms can be tested directly and improved. © 2012 The Wildlife Society.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.104 | 0.058 |
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".