Bibliographic record
Abstract
First, I would like to thank Mike Thicke (2011) for his very perceptive and civil review of Science: The Art of Living. He himself alludes to the difficulty that reviewers have had with my previous books defending intelligent design as a necessary condition for the possibility of science, a point I have discussed in this journal (Fuller 2008b). Fuller (2010) has no less polarised reviewers. Here readers are invited to contrast the rather sophisticated critical review of Science that has already appeared in Notre Dame Philosophical Reviews (Fagan 2011) and the bigoted one in Quarterly Review of Biology (Malaterre 2011), which ascribes to me views I make a point of denying. Both reviews appeared in high-profile venues in their respective fields and both were written by younger people trained in both philosophy and biology. I am happy to let future historians sort this one out.
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 | 0.012 | 0.076 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.057 | 0.081 |
| Insufficient payload (model declined to judge) | 0.019 | 0.015 |
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".