Data from: Positive relationships between association strength and phenotypic similarity characterize the assembly of mixed-species bird flocks worldwide
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
Competition theory predicts that communities at small spatial scales should consist of species more dissimilar than expected by chance. We find a strikingly different pattern in a multi-continent dataset (55 presence-absence matrices from 24 locations) on the composition of mixed-species bird flocks, important subunits of local bird communities the world over. Using null models and randomization tests followed by meta-analysis, we find the association strength of species in flocks to be strongly related to similarity in body size and foraging behavior, and higher for congeneric compared with non-congeneric species pairs. Given the small spatial scale of our individual analyses, differences in habitat preferences of species are unlikely to have caused these association patterns; therefore, the patterns are most likely the outcome of species interactions. Extending group-living and social information use theory to a heterospecific context, we discuss potential behavioral mechanisms leading to positive interactions among similar species in flocks as well as ways in which competition costs are reduced. Our findings highlight the need to consider positive interactions along with competition when seeking to explain community assembly.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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