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Record W2173914599 · doi:10.1579/0044-7447-38.3.130

Human Modification of a Large Meandering Amazonian River: Genesis, Ecological and Economic Consequences of The Masisea Cutoff on the Central Ucayali, Peru

2009· article· en· W2173914599 on OpenAlex
Oliver T. Coomes, Christian Abizaid, Michel Lapointe

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAMBIO · 2009
Typearticle
Languageen
FieldArts and Humanities
TopicAmazonian Archaeology and Ethnohistory
Canadian institutionsMcGill University
Fundersnot available
KeywordsAmazonianGeographyGeologyEcologyAmazon rainforestBiology

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.931
Threshold uncertainty score0.609

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.037
GPT teacher head0.248
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it