Maximum likelihood spectral fitting and its application to EBL constraints
Bibliographic record
Abstract
The extragalactic background light (EBL) is the second-most-intense form of cosmic background light (the first being the cosmic microwave background) and contains the redshifted optical radi- ation, from infra-red to ultraviolet, emitted across all epochs, making it of great cosmological in- terest. While direct measurements of the EBL are hampered by foreground contamination, obser- vations of VHE emission from distant sources can be used to obtain indirect measurements of the EBL. In this work a maximum-likelihood fit is applied to the energy spectra of blazars observed by VERITAS, an array of ground-based imaging atmospheric Cherenkov telescopes sensitive to very-high-energy (VHE; E>100 GeV) gamma rays. Using theoretical models of the EBL shape and intensity, the EBL normalization is treated as a free parameter, allowing for model-dependent constraints to be obtained. Details of this maximum-likelihood analysis and preliminary model- dependent constraints on the EBL, are presented.
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How this classification was reachedexpand
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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".