Bibliographic record
Abstract
There's no getting blood out of a turnip. Captain Marryat INTRODUCTION On ‘the very idea of an ontological proof’ 1.1.1. Ontological arguments would be demonstrations of God's existence, deductions from scratch without aid of contingent premises. But cannot such existence proofs be rejected out of hand and without detailed consideration on the general ground that it is not possible to demonstrate the existence of anything? This has been said. Cleanthes : [T]here is an evident absurdity in pretending to demonstrate a matter of fact, or to prove it by any arguments a priori . Nothing is demonstrable unless the contrary implies a contradiction. Whatever we conceive as existent, we can also conceive as non-existent. There is no being, therefore, whose non-existence implies a contradiction. Consequently there is no being whose existence is demonstrable. I propose this as entirely decisive. (Hume 1991, Part 10, p. 149) However, while certainly nothing is demonstrable that is not itself necessary, it does not follow from that that there is nothing whose existence is demonstrable, for there are things that exist necessarily. For example, the number 23: It is necessary that there exists a prime number greater than 20 and less than 25, and it is 23. “But surely,” Cleanthes might complain, “you quibble. For no one supposes that God is a number, or anything like one.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.028 | 0.006 |
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".