Animalcules: The Activities, Impacts, and Investigators of Microbes By Bernard Dixon Washington, DC: ASM Press, 2009. 358 pp. $39.95 (hardcover).
Bibliographic record
Abstract
Animalcules is a compilation of essays by Bernard Dixon that have appeared in the American Society for Microbiology journal Microbes. As a result, one can read this book in a number of manners. In a somewhat academic manner, one could theoretically scan the table of contents for a topic and learn something about Botox, frescoes, or Gerhard Domagk. I fear that this would miss the point in an era when PubMed and Google Scholar can readily uncover articles on most any subject with a few keystrokes followed by a click of a search button. Instead, I would recommend a less directed read, such as flipping through essays on evolution by Stephen Jay Gould or reflections on biology by Lewis Thomas. One option is to open the book at random and enjoy a 4–5-page rumination on some microbiological topic that has likely never occurred to you (bedtime reading). Alternatively, one can read the book in its entirety, to get a sense of the common conceptual themes that recur (holiday reading).
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 | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.059 | 0.052 |
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".