MétaCan
Menu
Back to cohort
Record W4392386308 · doi:10.1139/cjz-2023-0132

Expect the unexpected: a new species of killifish from a highly stochastic temporary wetland near Iguazú Falls (Cyprinodontiformes: Rivulidae)

2024· article· en· W4392386308 on OpenAlexvenueno aff
Felipe Alonso, Guillermo Terán, Pablo Calviño, Wilson S. Serra, Martín Miguel Montes, Ignacio García, Jorge Barneche, Liliana Ciotek, Pablo Giorgis, Jorge Rafael Casciotta

Bibliographic record

VenueCanadian Journal of Zoology · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicFish biology, ecology, and behavior
Canadian institutionsnot available
FundersAgencia Nacional de Promoción de la Investigación, el Desarrollo Tecnológico y la Innovación
KeywordsCyprinodontiformesBiologyEcoregionEcologyKillifishEndemismWetlandHabitatGambusiaZoologyFisheryFish <Actinopterygii>

Abstract

fetched live from OpenAlex

We describe Argolebias adrianae, a new species of killifish from a small temporary wetland in the Paraná Forest ecoregion with no regular or predictable temporal pattern of water availability. This habitat is in the Lower Iguazú River Basin, known for its high fish endemism, but until now, only two species of Rivulidae were reported from it, but from the Araucarian Forest ecoregion. The genus Argolebias was previously only known from the lower portions of the Paraguay, Paraná, and Uruguay basins and middle Paraná. The new species is distinguished from all congeners by its unique coloration, which includes a conspicuously dark grey anterior third portion of the dorsal fin and the absence of iridescent spots on the basal half of the pectoral fin in live adult males, as well as dark grey spots on the anterocentral portion of the flanks of females. Our phylogenetic analysis shows A. adrianae to be closely related to Argolebias guarani from the adjacent Middle Paraná basin. We also provide data on the ecology, ontogeny of coloration, and chorion ornamentation of this species. Our findings have important implications for understanding the biogeography, ecology, and evolution of mechanisms that enable organisms to thrive in highly stochastic environments like this one.

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)0.000
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 score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
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 head0.017
GPT teacher head0.216
Teacher spread0.199 · 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

Citations11
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of ZoologySame topicFish biology, ecology, and behaviorFrench-language works237,207