Data from: Would an RRS by any other name sound as RAD?
Bibliographic record
Abstract
1. Sampling markers throughout a genome with restriction enzymes emerged in the 2000s as reduced representation shotgun sequencing (RRS). Rapid advances in sequencing technology have since spurred modifications of RRS, giving rise to many derivatives with unique names, such as restriction site-associated DNA sequencing (RADseq). But naming conventions have often been more creative than consistent and criteria for recognizing unique methods have been unclear, resulting in a proliferation of names characterized by ambiguity. 2. We give an overview of methodological and etymological relationships among 36 restriction enzyme-based methods, and survey the consistency of references to five prominent methods in the literature. 3. We identified several instances of methodological convergence, and note that many published derivatives have modified only minor elements of parent protocols. Misattribution through ambiguous or inconsistent literature references was observed in 8.4% of journal articles citing the original one and two-enzyme RADseq and GBS, as well as SBG publications. 4. The rapid expansion of names associated with derivative protocols is confusing and, in many cases, unwarranted. We urge greater restraint in naming derivative methods and suggest general guidelines for naming that promote a balance between clarity, descriptiveness, and recognition of scientific innovation.
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.
How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 teacher head, 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".