MétaCan
Menu
Back to cohort
Record W2023136443 · doi:10.1073/pnas.230136397

Riverine barriers and the geographic distribution of Amazonian species

2000· article· en· W2023136443 on OpenAlexafffund
Claude Gascon, Jay R. Malcolm, James L. Patton, Maria Nazareth Ferreira da Silva, James P. Bogart, Stephen C. Lougheed, Carlos A. Peres, Selvino Neckel‐Oliveira, Peter T. Boag

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicFish biology, ecology, and behavior
Canadian institutionsUniversity of Guelph
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoNational Geographic SocietyNatural Sciences and Engineering Research Council of CanadaWildlife Conservation Society
KeywordsAmazonianSpecies richnessEcologyAmazon rainforestPhylogeographyGeographyDiversification (marketing strategy)BiologyPhylogenetics

Abstract

fetched live from OpenAlex

Rivers have been suggested to have played an important role in shaping present-day patterns of ecological and genetic variation among Amazonian species and communities. Recent molecular studies have provided mixed support for the hypothesis that large lowland Amazonian rivers have functioned as significant impediments to gene flow among populations of neotropical species. To date, no study has systematically evaluated the impact that riverine barriers might have on structuring whole Amazonian communities. Our analyses of the phylogeography of frogs and small mammals indicate that a putative riverine barrier (the Juruá River) does not relate to present-day patterns of community similarity and species richness. Rather, our results imply a significant impact of the Andean orogenic axis and associated thrust-and-fold lowland dynamics in shaping patterns of biotic diversity along the Juruá. Combined results of this and other studies significantly weaken the postulated role of rivers as major drivers of Amazonian diversification.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.245
Teacher spread0.230 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations286
Published2000
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicFish biology, ecology, and behaviorFrench-language works237,207