Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
If it had inherited a mutated gene that impaired its ability to run, then, relative to its companions, a deer would be defective and thus subject to selective devourment by predators. This is Tennyson’s “Nature, red in tooth and claw,” and Darwin’s “natural selection.” In 1862, shortly after reading Darwin’s Origin of Species by Means of Natural Selection while breeding sheep in New Zealand, the 27 year old Butler appeared to accept “the ordinary Darwinian argument,” albeit with some important caveats [2]: “That the immense differences between the camel and the pig should have come about in six thousand years is not believable; but in six million years it is not incredible.... Once grant the principles, once grant that competition is a great power in Nature, and that changes in circumstances and habits produce a tendency to variation in the offspring (no matter how slight that variation may be), and unless you can define the possible limit of such variation during an infinite series of generations, unless you can show that there is a limit, and that Darwin’s theory oversteps it, you have no right to object to his conclusions.”
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.
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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it