Bibliographic record
Abstract
Amazingly for a procedure so fundamental to present-day biomedical research as well as medical diagnostics, development of the western blot occurred within the memory of many individuals who continue to work in these fields. That is, conversely, there are many investigators and clinicians presently working who recall the days prior to the western blot. The personal stories of how and why the technique was developed are given in this volume by the people intimately involved with this development. These stories date from only roughly 30 years ago. Since then, a very large number of variations on the theme of gel separation of biologic products by different parameters such as size or charge, followed by transfer to solid support and identification, have been developed. The present compilation brings together a large number of these techniques, some of which are adaptations of the original technique in order to solve a problem, whereas others are far flung and vastly different from how the original techniques were envisioned. The goal of our work is to not only compile the vast array of techniques based on western blot, but also give practical methods. We suspect that almost everyone involved in the enterprise has tried to bring a new technique to their laboratory by reproducing methods found in traditional publications. Doing this is commonly fraught with difficulty and may take weeks to accomplish, or may be abandoned as impossible. We hope that investigators will be able to open this volume and rapidly begin to use a technique new to them and their laboratories because the chapters give detailed practical methods, tips, and alternatives. If you are able to open a chapter, and conveniently and quickly perform a new procedure in your laboratory, then we will have accomplished our goals in editing this work.
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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.008 | 0.005 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.013 | 0.010 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.009 | 0.008 |
| Research integrity | 0.005 | 0.015 |
| Insufficient payload (model declined to judge) | 0.064 | 0.114 |
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".