JDotter: a Java interface to multiple dotplots generated by dotter
Bibliographic record
Abstract
UNLABELLED: Java-Dotter (JDotter) is a platform-independent Java interactive interface for the Linux version of Dotter, a widely used program for generating dotplots of large DNA or protein sequences. JDotter runs as a client-server application and can send new sequences to the Dotter program for alignment as well as rapidly access a repository of preprocessed dotplots. JDotter also interfaces with a sequence database or file system to display supplementary feature data. Thus, JDotter greatly simplifies access to dotplot data in laboratories that deal with large numbers of genomes and have a multi-platform organization. AVAILABILITY: Currently, JDotter is used via Java Web Start by the Poxvirus Bioinformatics Resource for examining dotplots of complete poxvirus genomes; http://athena.bioc.uvic.ca/pbr/jdotter/. The software is available for download from the same location. SUPPLEMENTARY INFORMATION: Installation instructions, the User's Manual, screenshots and examples are available at the JDotter home page http://athena.bioc.uvic.ca/pbr/jdotter/. The software and source code is free for non-commercial applications.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.282 | 0.145 |
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".