Bibliographic record
Abstract
Abstract As I write these words, I am sitting in a hotel room in the Latin Quarter of Paris. Three hundred and fifty years ago or so this area was frequented by my people. I don’t mean my ancestors, who were in an altogether different part of Europe, doing very different things. I mean the people I study. In earlyand mid-seventeenth-century Paris you could find many of the people who made science and philosophy what it is today. Descartes lived here for a while; though he moved away, he came back from time to time, and his spirit (immaterial, of course) haunted these streets for many years. Pascal lived here, around the corner, actually. Mersenne lived across the river, in a neighborhood to which one could walk in thirty or forty-five minutes. I don’t know where Hobbes lived during the crucial decade of his life that he spent here, but it must have been close; Paris wasn’t that big back then. Ditto for Gassendi. A few years later Leibniz was to visit for three short years that shaped the rest of his intellectual life.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.040 | 0.007 |
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; both teacher heads agree on what is shown here.
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".