Ten must-read science histories <b>The Experiential Caribbean: Creating Knowledge and Healing in the Early Modern Atlantic</b> , <i>Pablo F. Gómez</i> , University of North Carolina Press, 2017, 314 pp. <b>Wild by Design: The Rise of Ecological Restoration</b> , <i>Laura J. Martin</i> , Harvard University Press, 2022, 336 pp. <b>The Making of Mr. Gray’s Anatomy: Bodies, Books, Fortune, Fame</b> , <i>Ruth Richardson,</i> Oxford University Press, 2008, 322 pp. <b>The Expressiveness of the Body and the Divergence of Greek and Chinese Medicine</b> , <i>Shigehisa Kuriyama,</i> Zone Books, 1999, 344 pp. <b>Networked Sovereignty: Building the Internet Across Indian Country</b> , <i>Marisa Elena Duarte</i> , University of Washington Press, 2017, 208 pp. <b>Secrets of Women: Gender, Generation, and the Origins of Human Dissection</b> , <i>Katharine Park</i> , Zone Books, 2006, 424 pp. <b>Bitter Roots: The Search for Healing Plants in Africa</b> , <i>Abena Dove Osseo-Asare</i> , University of Chicago Press, 2014, 288 pp. <b>The Measure of All Things: The Seven-Year Odyssey and Hidden Error That Transformed the World</b> , <i>Ken Alder</i> , Free Press, 2003, 448 pp. <b>Mind Fixers: Psychiatry’s Troubled Search for the Biology of Mental Illness</b> , <i>Anne Harrington,</i> Norton, 2020, 384 pp. <b>The PKU Paradox: A Short History of a Genetic Disease</b> , <i>Diane B. Paul and Jeffrey P. Brosco</i> , Johns Hopkins University Press, 2013, 320 pp.
Bibliographic record
Abstract
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.012 | 0.014 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.055 | 0.010 |
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".