Expect the unexpected: a new species of killifish from a highly stochastic temporary wetland near Iguazú Falls (Cyprinodontiformes: Rivulidae)
Bibliographic record
Abstract
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.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".