Bibliographic record
Abstract
An upper bound to the supernova relic neutrino background from all past type II supernovae is obtained using observations of the universal metal enrichment history. We show that an unambiguous detection of these relic neutrinos by the SuperKamiokande detector is unlikely. We also analyze the event rate in the Sudbury Neutrino Observatory (where coincident neutrons from ${\overline{\ensuremath{\nu}}}_{e}\stackrel{\ensuremath{\rightarrow}}{D}{\mathrm{nne}}^{+}$ might enhance background rejection), and arrive at the same conclusion. If the relic neutrino flux should be observed to exceed our upper bound and if the observations of the metal enrichment history (for $z<1)$ are not in considerable error, then either the type II supernova rate does not track the metal enrichment history or some mechanism may be responsible for transforming ${\overline{\ensuremath{\nu}}}_{\ensuremath{\mu},\ensuremath{\tau}}\ensuremath{\rightarrow}{\overline{\ensuremath{\nu}}}_{e}.$
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".