The Importance of Even Highly Incomplete Fossil Taxa in Reconstructing the Phylogenetic Relationships of the Tetraodontiformes (Acanthomorpha: Pisces)
Bibliographic record
Abstract
The use of fossils in the phylogenetics of extant clades traditionally has been a contentious issue. Fossils usually are relatively incomplete, and their use commonly leads to an increase in the number of equally most parsimonious trees and a decrease in the resolution of phylogenies. Fossils alone, however, provide certain kinds of information about the biological history of a clade, and computer simulations have shown that even highly incomplete material can, under certain circumstances, increase the accuracy of a phylogeny, rather than decrease it.Because empirical data are still scarce on the effects of the inclusion of fossils on phylogenetic reconstructions, we attempted to investigate this problem by using a relatively well-known group of acanthomorph fishes, the Tetraodontiformes (triggerfishes, pufferfishes, and ocean sunfishes), for which robust phylogenies using extant taxa already exist and that has a well-studied fossil record. Adding incomplete fossil taxa of tetraodontiforms usually increases the number of equally most parsimonious trees and often decreases the resolution of consensus trees. However, adding fossil taxa may help to correctly establish relationships among lineages that have experienced high degrees of morphological diversification by allowing for a reinterpretation of homologous and homoplastic features, increasing the resolution rather than decreasing it. Furthermore, taxa that were scored for 25% or more of their characters did not cause a significant loss of resolution, while providing unique biological information.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".