DNA Barcoding Birds: From Field Collection to Data Analysis
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
As of February 2011, COI DNA barcode sequences (a 648-bp segment of the 5' end of the mitochondrial gene cytochrome c oxidase I, the standard DNA barcode for animals) have been collected from over 23,000 avian specimens representing 3,800 species, more than one-third of the world's avifauna. Here, we detail the methodology for obtaining DNA barcodes from birds, covering the entire process from field collection to data analysis. We emphasize key aspects of the process and describe in more detail those that are particularly relevant in the case of birds. We provide elemental information about collection of specimens, detailed protocols for DNA extraction and PCR, and basic aspects of sequencing methodology. In particular, we highlight the primer pairs and thermal cycling profiles associated with successful amplification and sequencing from a broad range of avian species. Finally, we succinctly review the methodology for data analysis, including the detection of errors (such as contamination, misidentifications, or amplification of pseudogenes), assessment of species resolution, detection of divergent intraspecific lineages, and identification of unknown specimens.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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