Bibliographic record
Abstract
Context: Landscape fragmentation, which has demonstrated links to habitat loss, increased isolation, a loss of connectivity, and decreased biodiversity, is difficult to quantify. Traditional pattern-based approaches to measuring fragmentation use landscape metrics to quantify aspects of the composition or configuration of landscapes. Objective: The objective of this study was to examine the relative improvements of an alternative activity-based approach using the cost of traversing a landscape as a proxy for fragmentation and compare it with the traditional approach. Methods: One thousand binary landscapes varying in composition and configuration were simulated, and least-cost path analysis provided the data to calculate the activity-based metrics, which were compared with computed traditional pattern-based metrics. Results: Activity-based fragmentation assessments were sensitive to levels of landscape fragmentation, but offered improvements over exiting pattern-based methods in that some metrics varied monotonically across the spectrum of landscape configurations and thus makes their interpretation more holistically meaningful. Conclusions: This study provides a modular conceptual framework for assessing fragmentation using activity-based metrics that offer functional improvements over existing pattern-based approaches. While we present a focused theoretical implementation, the process to be measured and the scale of observation can be altered to suit specific user requirements, ecosystems, or species of interest.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".