Minima of sequences of Gaussian random variables
Bibliographic record
Abstract
For a given sequence of real numbers a 1 , … , a n we denote the k -th smallest one by k - min 1 ⩽ i ⩽ n a i . We show that there exist two absolute positive constants c and C such that for every sequence of positive real numbers x 1 , … , x n and every k ⩽ n one has c max 1 ⩽ j ⩽ k k + 1 − j ∑ i = j n 1 / x i ⩽ E k - min 1 ⩽ i ⩽ n | x i g i | ⩽ C ln ( k + 1 ) max 1 ⩽ j ⩽ k k + 1 − j ∑ i = j n 1 / x i , where g i ∈ N ( 0 , 1 ) , i = 1 , … , n , are independent Gaussian random variables. Moreover, if k = 1 then the left hand side estimate does not require independence of the g i s. Similar estimates hold for E k - min 1 ⩽ i
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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 | 0.003 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".