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Record W2992122671 · doi:10.1590/1982-0224-20190118

Upstream dam impacts on gilded catfish Brachyplatystoma rousseauxii (Siluriformes: Pimelodidae) in the Bolivian Amazon

2019· article· en· W2992122671 on OpenAlexfundno aff
Paul A. Van Damme, Leslie Córdova-Clavijo, Claudio Baigún, Marília Hauser, Carolina Rodrigues da Costa Dória, Fabrice Duponchelle

Bibliographic record

VenueNeotropical Ichthyology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicFish biology, ecology, and behavior
Canadian institutionsnot available
FundersVlaamse Interuniversitaire RaadCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorInternational Development Research Centre
KeywordsCatfishFisheryAmazon rainforestGeographyHydrology (agriculture)BiologyFish <Actinopterygii>EcologyGeology

Abstract

fetched live from OpenAlex

ABSTRACT This paper explores the effects of two run-of-river dams (Jirau and Santo Antônio) built in cascade in the middle Madeira River (Brazil) on the interruption of long-distance migration routes of the gilded catfish (Brachyplatystoma rousseauxii). A participative monitoring system was set up to compare capture by commercial fishers approximately 1500 km upstream of the dams in Bolivia, before (1998-2007) and after (2015-2017) dam closure. A significant decrease in gilded catfish catches and in catch per unit effort was observed after dam closure, whereas no significant difference in mean weight was found. Back-estimation of age suggests that the few individuals remaining after dam closure in 2009 are a mixture of old homers that returned upstream before dam closure, and residents hatched after dam closure and trapped in the upper Madeira. Unless fishways in the Madeira River dams improve their efficiency, the gilded catfish might become rare and in danger of regional extinction in the upper Madeira basin in the next few years, negatively affecting river fisheries.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.997

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.007

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 head0.010
GPT teacher head0.247
Teacher spread0.236 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations33
Published2019
Admission routes1
Has abstractyes

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