FluDen Primer DB –PCR Primer Database for Influenza A and Dengue Virus
Bibliographic record
Abstract
FluDen Primer Database (http://www.fludenpdb.com) has been designed and developed as a web application program to provide free access to the in-silico designed multiple potential primers for PCR detection and quantification assays for Influenza and dengue viruses.This program also permits user to submit sequence of their choice for primer design.The database contains primer records for Influenza and dengue viruses which cause infection in Humans.As of 2014 there are 142 primer sets for screening 32 genes/regions of Influenza and dengue viruses together.Application contain gene information, assay details such as oligonucleotide sequence, primer properties and reaction conditions, publication information.We have developed a resource, FluDen Primer DB which contains primer that can be used for PCR under provided amplification conditions for each primer pair.A distinguish feature of the FlueDen is the primers listed in DB are the products of PCR design application which are experimentally validated.Primers for the FluDen were designed using current genomic information available from the National Center for Biotechnology Information (NCBI).
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.050 | 0.062 |
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".