Rphylip: an<scp>R</scp>interface for<scp>PHYLIP</scp>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Summary The phylogeny methods software package PHYLIP has long been among the most widely used packages for phylogeny inference and phylogenetic comparative biology. Numerous methods available in PHYLIP , including several new phylogenetic comparative analyses of considerable importance, are not implemented in any other software. Over the past decade, the popularity of the R statistical computing environment for many different types of phylogenetic analyses has soared, particularly in phylogenetic comparative biology. There are now numerous packages and methods developed for the R environment. In this article, we present Rphylip, a new R interface for the PHYLIP package. Functions of Rphylip interface seamlessly with all of the major analysis functions of the PHYLIP package. This new interface will enable the much easier use of PHYLIP programs in an integrated R workflow. In this study, we describe our motivation for developing Rphylip and present an illustration of how functions in the Rphylip package can be used for phylogenetic analysis in R.
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.
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 | 0.003 | 0.003 |
| 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