DNA Barcoding, species delineation and taxonomy: a historical perspective
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
Abstract DNA barcoding is a system designed to provide species identification by using standardized gene regions as internal species tag. Foreseen since its earlier development as a solution to speed up the pace of species discovery, DNA barcoding has established as a mature field of biodiversity sciences filing the conceptual gap between traditional taxonomy and different fields of molecular systematics. Initially proposed as a tool for species identification, DNA barcoding has also been applied in taxonomy routines for automated species delineation. Species identification and species delineation, however, should be considered as distinct activities relying on different theoretical and methodological backgrounds. The aim of the present review is to provide an overview of the use of DNA sequences in taxonomy, since the earliest development of molecular taxonomy until the development of DNA barcoding. We further present the differences between procedures of species identification and species delineation and highlight how DNA barcoding proposed a new paradigm that helps promote more sustainable practices in taxonomy.
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 | 0.000 | 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