To what extent do new fossil discoveries change our understanding of clade evolution? A cautionary tale from burying beetles (Coleoptera:<i>Nicrophorus</i>)
Why this work is in the frame
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Bibliographic record
Abstract
Divergence time estimates derived from phylogenies are crucial to infer historical biogeography and diversification dynamics. Yet, the impact of fossil record incompleteness on macroevolutionary reconstructions remains equivocal. Here, we investigate to what extent gaps in the fossil record can impinge downstream evolutionary inferences in the beetle family Silphidae. Recent discoveries have pushed back the fossil record of this group from the Eocene into the Jurassic. We estimated the divergence times of the family using both its currently understood fossil record and the fossil record known prior to these recent discoveries. All fossil calibrations were informed with different parametric distributions to investigate the weight of priors on posterior age estimates. Based on time-calibrated trees, we assessed the impact of fossil calibrations on the inference of ancestral ranges and diversification rate dynamics in the genus Nicrophorus. Depending upon the selected sets of fossil constraints, the age discrepancies had a major impact on the macroevolutionary inferences: the biogeographic extrapolations relative to paleogeography are markedly contrasting, and the calculated rates at which species form or go extinct (and when they varied) are strikingly different. We show that soft prior distributions do not necessarily alleviate such shortcomings therefore preventing the inference of reliable macroevolutionary patterns in groups presenting a taphonomic bias in their fossil record.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it