DNA barcoding on Oxford Nanopore: multiplexing up to 24 x 96-well plates v1
Bibliographic record
Abstract
This protocol describes laboratory methods for sequencing a standard COI marker (i.e. DNA barcoding), multiplexing up to 2,280 specimens (24 x 96 well plates, with one negative control well per plate), to run on an Oxford Nanopore Technologies Flongle 10.4.1 Flow Cell on a MinION sequencer. All indexing is accomplished by PCR using tagged primers, meaning that library prep is only carried out in a single tube with all 2,280 PCRs pooled. This is accomplished by asymmetrical indexing, where forward primers carrying 96 Unique Molecular Identifiers (UMIs) provide mapping to a well of a 96-well plate, and reverse primers with 24 UMIs provide mapping to the plate. The protocol details all primer sequences (attached as a text table) and gives instructions for manufacturing batches of pre-made indexed plates, carrying out PCR, pooling and library prep for the ONT platform, and loading onto the sequencing device.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.044 | 0.058 |
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".