Human Modification of a Large Meandering Amazonian River: Genesis, Ecological and Economic Consequences of The Masisea Cutoff on the Central Ucayali, Peru
Bibliographic record
Abstract
Evidence is mounting regarding the significant extent and scope of long-term human modification of "pristine nature" in the neotropics. In Amazonia, recent studies point to the landscape imprint of human activity that has transformed the forests, savannas, soils, and waterways of the basin. In this report, we describe a massive meander cutoff in the Peruvian Amazon along the Ucayali River--the fifth-longest river in the Amazon basin--that was triggered by small-scale human actions and resulted in significant ecological and economic consequences for the region. The modern case of the Masisea cutoff-near the Amazonian port city of Pucallpa, Peru (285,000 inhabitants)-indicates that humans using simple tools can play a major role in transforming large meandering rivers and their floodplains.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".