Increasing global participation in genetics research through DNA barcoding
Bibliographic record
Abstract
DNA barcoding--the sequencing of short, standardized DNA regions for specimen identification and species discovery--has promised to facilitate rapid access to biodiversity knowledge by diverse users. Here, we advance our opinion that increased global participation in genetics research is beneficial, both to scientists and for science, and explore the premise that DNA barcoding can help to democratize participation in genetics research. We examine publication patterns (2003-2014) in the DNA barcoding literature and compare trends with those in the broader, related domain of genomics. While genomics is the older and much larger field, the number of nations contributing to the published literature is similar between disciplines. Meanwhile, DNA barcoding exhibits a higher pace of growth in the number of publications as well as greater evenness among nations in their proportional contribution to total authorships. This exploration revealed DNA barcoding to be a highly international discipline, with growing participation by researchers in especially biodiverse nations. We briefly consider several of the challenges that may hinder further participation in genetics research, including access to training and molecular facilities as well as policy relating to the movement of genetic resources.
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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) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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".