Evidence of parallel evolution in the dental elements of <i>Sweetognathus</i> conodonts
Bibliographic record
Abstract
The repeated emergence of similar morphologies in the dental elements of Permian Sweetognathus conodonts has been a hypothesized example of parallel evolution. To test if morphological parallelisms occur between isolated Sweetognathus lineages, this study uses two-dimensional-based geometric morphometrics combined with a revised and expanded phylogeny of Permian Sweetognathus conodonts to quantify dental element trait distributions and compare the phenotypic trajectories between lineages. A hierarchical clustering method was used to identify recurrent species pairs based on principal component scores describing their morphological variation, with the further incorporation of widely used ecological metrics such as limiting similarity and morphological overlap. Our research implies that a major contributor to conodont diversity in Palaeozoic marine trophic networks is the emergence of recurrent parallel morphologies via disruptive and directional selection. This study illustrates the mechanisms through which conodonts achieved their status as hyper-diverse predators and scavengers, contributing substantially to the complexity of Palaeozoic marine communities.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".