Bibliographic record
Abstract
Distributed by Redasoft, Toronto, Canada (http://www.redasoft.com) This is a new map-drawing and sequence analysis package from Redasoft. In its web pages the company promises that it has been designed to be intuitive, comprehensive and affordable, and without doubt these goals have been achieved to a very large degree; Visual Cloning 2000 is a substantial improvement on Plasmid, their previous package. Sequences can be imported from files, copied from the clipboard, downloaded from the internet as new maps, or inserted into pre-existing maps and several maps can be displayed at one time. The display interface is clear and easy to understand; all function menus are displayed as large buttons. An excellent integral web-browser facilitates access of sequences via the National Centre for Biotechnology Information (NCBI), Sequence Retrieval System (SRS), or Redasoft cloning vector search engines. However, unlike other packages, Visual Cloning 2000 contains no database of commonly used vector sequences to save searching for vector sequences and assist in the creation of the vast majority of construct maps. Several simple tools for sequence analysis and experiment design are included. A sequence viewer enables sequences to be viewed simultaneously as text and graphics, but this function is read-only. There are also tools for PCR primer design, subsequence searching, restriction analysis and prediction of open reading frames; these aren’t novel, but they quite adequate and very easy to use. The main strongpoint of the package is, however, the quality of the vector/insert maps. These are not only very clear, and rival those produced with more powerful packages, but can be manipulated easily to contain primer binding and restriction enzyme sites. In addition, they can be pasted into other desktop applications such as Word and Powerpoint without format alterations. Visual Cloning 2000 is a sophisticated, user-friendly, mid-priced plasmid drawing package with limited analytical capabilities. It does not replace complex software suits such as Wisconsin Package (Genetics Computer Group Inc.) for hard-core sequence analysis and gene prediction, but its ease of use will ensure it a place on many a crowded computer desktop.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.256 | 0.164 |
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".