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Record W6929554882 · doi:10.48550/arxiv.hep-ph/0309100

Evidence for Mikheyev-Smirnov-Wolfenstein effects in solar neutrino flavor transitions

2003· preprint· en· W6929554882 on OpenAlexaboutno aff

Bibliographic record

VenuearXiv (Cornell University) · 2003
Typepreprint
Languageen
FieldChemistry
TopicAdvanced Proteomics Techniques and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsSolar neutrinoNeutrinoNeutrino oscillationSolar neutrino problemAmplitudeMeasurements of neutrino speedPoint (geometry)

Abstract

fetched live from OpenAlex

We point out that the recent data from the Sudbury Neutrino Observatory, together with other relevant measurements from solar and reactor neutrino experiments, convincingly show that the flavor transitions of solar neutrinos are affected by Mikheyev-Smirnov-Wolfenstein (MSW) effects. More precisely, one can safely reject the null hypothesis of no MSW interaction energy in matter, despite the fact that the interaction amplitude (formally treated as a free parameter) is still weakly constrained by the current phenomenology. Such a constraint can be improved, however, by future data from the KamLAND experiment. In the standard MSW case, we also perform an updated analysis of two-family active oscillations of solar and reactor neutrinos.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.086
GPT teacher head0.238
Teacher spread0.152 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2003
Admission routes1
Has abstractyes

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