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 forIniaandSotaliaover 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 ofIniaoccurred 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.
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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) | 0.002 | 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".