Most Commons in Pathology and Laboratory Medicine. Edward F. Goljan. Philadelphia, PA: WB Saunders Company, 1999, 516 pp., $19.95. ISBN 0-7216-7992-7.
Bibliographic record
Abstract
This superb, inexpensive pocket book provides answers to a wide variety of the most common questions in pathology and laboratory medicine. Most aspects of the discipline are covered, including principles of pathology such as cell injury, inflammation, immunopathology, nutrition, genetics, environmental pathology, and neoplasia. Systematic pathology is described under the usual headings, as is clinical pathology: clinical chemistry (I wish books would stop using mEq/L for electrolytes), hematopathology, and immunohematology. Some microbiology is included in relation to the above sections, but this discipline does not command a section of its own. The book is intended as a study guide to the larger Saunders pathology text, which is also a very affordable book (1). Most Commons in Pathology and Laboratory Medicine provides common questions and answers in table format. A multiple choice question is included at the end of each section, followed by a brief discussion of the correct answer. It places a heavy emphasis on pathophysiology and mechanisms of disease. I found this booklet surprisingly comprehensive and very useful. As in any synopsis, corners are cut, and the obsessive reader may challenge some of the conclusions, but I found it accurate in the areas in which I have special expertise. Readers who require more depth must read the parent text. “The proof of the pudding is in the eating thereof”; I keep it by me and read a few pages each day and have learned a great deal in a short time. If I were preparing for exams, I would find it invaluable.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.279 | 0.305 |
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".