Rphylip: an<scp>R</scp>interface for<scp>PHYLIP</scp>
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.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.007 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.204 | 0.192 |
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".