Contributors
Bibliographic record
Abstract
In midcareer, he became enchanted with electromechanical cipher machines, and he recently realized a long-held goal of refurbishing the legendary HX-63, which he describes on page 32. He now lives in Paris, where he is active in the Association des Rservistes du Chiffre et de la Scurit de l'Information, a French association of cryptographers and information-security professionals. OLGA USKOVA Uskova is a Russian tech entrepreneur and investor. She is the founder and president of Cognitive Technologies Group and the CEO of Cognitive Pilot (a joint venture with SberBank) whose autonomous combine harvesters are featured on page 40. Uskova is also a founder of the Russian Abstract Art Foundation, aimed at supporting academic and historical understanding of Russian abstract art in a global context. CORRECTION: There were several editing errors in "An Antenna Made for an Icy, Radioactive Hell" [August 2021]. The two Mars orbiters' transmission power is on the order of 100 watts. The Europa antenna's array has 16 8-by-8 subarrays. While the unit cells can handle only a few watts, each subarray itself can handle more than 100 W. We also incorrectly suggested that the Europa antenna design would not need to be reoriented to send signals.
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 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.434 | 0.333 |
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; the direct Gemma label and the distilled Codex classifier 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".