Ecological factors influencing group sizes of river dolphins (<i>Inia geoffrensis</i>and<i>Sotalia fluviatilis</i>)
Bibliographic record
Abstract
Abstract Living in groups is usually driven by predation and competition for resources. River dolphins do not have natural predators but inhabit dynamic systems with predictable seasonal shifts. These ecological features may provide some insight into the forces driving group formation and help us to answer questions such as why river dolphins have some of the smallest group sizes of cetaceans, and why group sizes vary with time and place. We analyzed observations of group size for Inia and Sotalia over a 9 yr period. In the Amazon, largest group sizes occurred in main rivers and lakes, particularly during the low water season when resources are concentrated; smaller group sizes occurred in constricted waters (channels, tributaries, and confluences) that receive an influx of blackwaters that are poor in nutrients and sediments. In the Orinoco, the largest group sizes occurred during the transitional water season when the aquatic productivity increases. The largest group size of Inia occurred in the Orinoco location that contains the influx of two highly productive whitewater rivers. Flood pulses govern productivity and major biological factors of these river basins. Any threats to flood pulses will likely have an effect on the functionality of these ecosystems and the species living in them.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".