Datasets and R codes: An empirical test of the relative and combined effects of land-cover and climate change on local colonization and extinction
Bibliographic record
Abstract
This fileset includes the R code and associated data used in Yalcin & Leroux (2018). Yalcin, S. and Leroux, S. J. (2018), An empirical test of the relative and combined effects of land‐cover and climate change on local colonization and extinction. Glob Change Biol. doi:10.1111/gcb.14169 Thanks to all data providers:Ontario Breeding Bird Atlas (Bird Studies Canada, Canadian Wildlife Service, Federation of Ontario Naturalists, Ontario Field Ornithologists, and Ontario Ministry of Natural Resources) for supplying Atlas data, and to the thousands of volunteer participants who gathered data for the project, and Cadman et al. (1987; 2007);Natural Resource Canada and McKenney et al. (2011) for supplying climate data;Global Forest Watch Canada and Lee (2007) for publicly sharing datasets of anthropogenic changes;Food and Agriculture Organization of the United Nations and Bai et al. (2008) for publicly sharing data of net primary productivity changes. The raw datasets can be found: Ontario Breeding Bird Atlas:Website: http://www.birdsontario.org/atlas/index.jspCadman M. D., Eagles, P. F. J., Helleiner, F. M. (Eds.) (1987) Atlas of Breeding Birds of Ontario 1980-1985. Waterloo, Canada: University of Waterloo Press.Cadman M. D., Sutherland, D. A., Beck G. G., Lepage D., Couturier, A. R. (Eds.) (2007) Atlas of Breeding Birds of Ontario 2001-2005. Toronto, Canada: Bird Studies Canada, Environment Canada, Ontario Field Ornithologists, Ontario Ministry of Natural Resources, Ontario Nature.Climate data: McKenney, D. W., Hutchinson, M. F., Papadopol, P. et al., (2011) Customized spatial climate models for North America. Bulletin of the American Meteorological Society, 92, 1611-1622. Global Forest Watch Canada:Website: http://www.globalforestwatch.ca/data/20101210ALee P. (2007) Recent Anthropogenic Changes within the Boreal Forests of Ontario and Their Potential Impacts on Woodland Caribou (A Global Forest Watch Canada Report). Edmonton, Canada: Global Forest Watch Canada.Changes in net primary productivity:Bai Z., Dent D., Olsson L., Schaepman M. (2008) Proxy global assessment of land degradation. Soil Use and Management, 24, 223–234.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.014 | 0.113 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.133 | 0.087 |
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".