Refinements for the amplification and sequencing of red algal DNA barcode and RedToL phylogenetic markers: a summary of current primers, profiles and strategies
Bibliographic record
Abstract
This review provides a comprehensive summary of the PCR primers and profiles currently in use in our laboratory for red algal DNA barcoding and phylogenetic research. While work focuses on florideophyte taxa, many of the markers have been applied successfully to the Bangiales, as well as other lineages previously assigned to the Bangiophyceae sensu lato. All of the primers currently in use with their respective amplification profiles and strategies are provided, which can include full fragment, overlapping fragments and what might best be called "informed overlapping fragments", i.e., a fragment for a marker is amplified and sequenced for a taxon and those sequence data are then used to identify the best primers to amplify the remaining fragment(s) for that marker. We extend this strategy for the more variable markers with sequence from the external PCR primers used to "inform" the selection of internal sequencing primers. This summary will hopefully serve as a useful resource to systematists in the red algal community.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.022 |
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".