A critique of Thompson and Ramírez-Barahona (2023) or: how I learned to stop worrying and love the fossil record
Bibliographic record
Abstract
by Thompson and Ramírez-Barahona (2023) argued that, according to analyses of diversification on two massive molecular phylogenies comprising thousands of species, there is no evidence that angiosperms (i.e. flowering plants) were affected by the Cretaceous-Paleogene mass extinction. Here, I critique these conclusions from both methodological and philosophical perspectives. I demonstrate that the methods used in their study possess statistical limitations that strongly reduce the power to detect a true mass extinction event using data similar to those analysed by Thompson and Ramírez-Barahona (2023). Additionally, I use their study as a springboard to examine the relationship between phylogenetic and fossil evidence in diversification studies.
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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 | 0.046 | 0.147 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.036 |
| Scholarly communication | 0.009 | 0.016 |
| Open science | 0.008 | 0.007 |
| Research integrity | 0.017 | 0.035 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".