From the Zeno's paradoxes to novel immunotherapeutic agents for kidney cancer: moving from an era of wrong premises and conclusions to a better comprehension of immunology
Bibliographic record
Abstract
In the 5th century B.C., Zeno of Elea offered arguments that led to conclusions contradicting what we all know from our experience. The arguments were paradoxes for the ancient philosophers and it took centuries to demonstrate that they were not true. For example, in his Achilles and the tortoise paradox, fast running Achilles races to catch a slower tortoise that has a head start; so, if Achilles hopes to overtake the tortoise, he must run first to the place where the tortoise presently is, but by the time he arrives there, it would have crawled to a new place, so then Achilles must run to this new place, but the tortoise meanwhile will have crawled on, and so forth Achilles will never catch the tortoise, concludes Zeno. From this well known paradox, it appears clearly that from wrong premises come wrong conclusions, something that for years has affected our perception of the role of immunotherapy in kidney cancer.
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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 | 0.006 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.035 | 0.046 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".