Evaluating anthropogenic influence on a mesopredator: opossum (<i>Didelphis virginiana</i>) isotope values influenced by corn agriculture more than urbanization
Bibliographic record
Abstract
The composition of North American communities is changing due to anthropogenic land-use alteration. Mammalian mesopredators’ ability to consume anthropogenic trash due to their generalist diet has been referenced to partially explain their success in altered landscapes as they spread northward. We evaluated this assumption using carbon isotope values (δ13C) of the Virginia opossum ( Didelphis virginiana (Kerr, 1792)), a mesopredator expanding its range. δ13C values increase from consumption of C4 plants, including corn, a common food additive in North America. Opossum hairs from the Midwestern U.S. and Northeast were evaluated using generalized linear mixed models (GLMMs) to compare the predictive performances between winter harshness variables and anthropogenic variables. We also evaluated δ13C values through time to test if the temporal pattern of increased corn additives is mirrored in northern opossums. The best-performing GLMM included year and percentage corn fields as positive covariates. Variance in δ13C values increased exclusively in the “cornbelt” Midwest after 1970. δ13C values compared across space and time bolster evidence for the influence of agricultural development on the opossum’s range expansion.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 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 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".