Irreversible Markov processes for phylogenetic models
Why this work is in the frame
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Bibliographic record
Abstract
Abstract A frequently used model in phylogenetics uses a discrete Markov process to model molecular drift as a cause of evolutionary diversification. Predictions are often based on eigenvalue computations which, we argue, only make sense if the process is reversible. Since there is no evidence (to our knowledge) to support the reversible nature of the process, a re‐examination is made of the model and necessary algorithms with emphasis on irreversible processes. The paper includes careful discussion of the underlying Markov processes, careful distinction between the properties of reversible and irreversible processes (including earlier widely accepted analysis) all in the language of linear algebra, a new least squares approach to data adjustments, and numerical examples. Copyright © 2003 John Wiley & Sons, Ltd.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 it