Bibliographic record
Abstract
Abstract The first solar neutrino experiment, led by Raymond Davis Jr, showed a deficit of neutrinos relative to the solar model prediction, referred to as the “solar neutrino problem” since the 1970s. The Kamiokande experiment, led by Masatoshi Koshiba, successfully observed solar neutrinos, as first reported in 1989. The observed flux of solar neutrinos was almost half the predicted value and confirmed the solar neutrino problem. This problem was not resolved for some time due to possible uncertainties in the solar model. In 2001, it was discovered that the solar neutrino problem is due to neutrino oscillations by comparing the Super-Kamiokande and Sudbury Neutrino Observatory results; this was the first model-independent comparison. Detailed studies of solar neutrino oscillations have since been performed, and the results of solar neutrino experiments are consistent with solar model predictions when the effects of neutrino oscillations are taken into account. In this article, the history of solar neutrino observations is reviewed with the contributions of Kamiokande and Super-Kamiokande detailed.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".