A sharp rearrangement inequality for the fractional maximal operator
Bibliographic record
Abstract
. We prove a sharp pointwise estimate of the nonincreasing rearrangement of the fractional maximal function of f , M fl f , by an expression involving the nonincreasing rearrangement of f . This estimate is used to obtain necessary and sufficient conditions for the boundedness of M fl between classical Lorentz spaces. 1. Introduction and statement of main results For n 2 N and fl 2 [0; n), the fractional maximal operator M fl is defined at f 2 L 1 loc (R n ) by (M fl f)(x) = sup Q3x jQj fl n \\Gamma1 Z Q jf(y)j dy; x 2 R n ; where the supremum is extended over all cubes Q ae R n with sides parallel to the coordinate axes and jEj denotes the n-dimensional Lebesgue measure of a measurable subset E of R n . For the classical Hardy--Littlewood maximal operator M := M 0 , the rearrangement inequality (1.1) cf (t) (Mf) (t) Cf (t); t 2 (0; 1); holds, where f (t) = inf n ? 0; jfx 2 R n ; jf(x)j ? gj t o is the nonincreasing rearrangement of f , f (t) = t...
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".