TIME-INTEGRATED SEARCHES FOR POINT-LIKE SOURCES OF NEUTRINOS WITH THE 40-STRING IceCube DETECTOR
Bibliographic record
Abstract
We present the results of time-integrated searches for astrophysical neutrino sources in both the northern and southern skies. Data were collected using the partially completed IceCube detector in the 40-string configuration recorded between 2008 April 5 and 2009 May 20, totaling 375.5 days livetime. An unbinned maximum likelihood ratio method is used to search for astrophysical signals. The data sample contains 36,900 events: 14,121 from the northern sky, mostly muons induced by atmospheric neutrinos, and 22,779 from the southern sky, mostly high-energy atmospheric muons. The analysis includes searches for individual point sources and stacked searches for sources in a common class, sometimes including a spatial extent. While this analysis is sensitive to TeV–PeV energy neutrinos in the northern sky, it is primarily sensitive to neutrinos with energy greater than about 1 PeV in the southern sky. No evidence for a signal is found in any of the searches. Limits are set for neutrino fluxes from astrophysical sources over the entire sky and compared to predictions. The sensitivity is at least a factor of two better than previous searches (depending on declination), with 90% confidence level muon neutrino flux upper limits being between E 2 d Φ/ dE ∼ 2–200 × 10 −12 TeV cm −2 s −1 in the northern sky and between 3–700 × 10 −12 TeV cm −2 s −1 in the southern sky. The stacked source searches provide the best limits to specific source classes. The full IceCube detector is expected to improve the sensitivity to d Φ/ dE ∝ E −2 sources by another factor of two in the first year of operation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".