Data Release: Measurement of neutron production in atmospheric neutrino interactions at Super-Kamiokande
Bibliographic record
Abstract
This data release accompanies the article ["Measurement of neutron production in atmospheric neutrino interactions at Super-Kamiokande"](https://arxiv.org/abs/2505.04409). The data provided here includes observed average neutron multiplicity in atmospheric neutrino interactions at Super-Kamiokande (SK) as a function of the event's visible energy, along with model predictions using various combinations of final-state interaction (FSI) models and secondary hadron interaction models. For details on the data selection and compared models, please refer to the associated article on [arXiv](https://arxiv.org/abs/2505.04409). Files Included: 1. `x_bin_edges.txt`:Contains the x bin edges for all data, formatted as a list, which is equivalent to `np.logspace(np.log10(30), 4, 51)` in `numpy`. The bin edges are common for all event types included in the two comma-delimited csv files below. 2. `data_observations.csv`:Contains the observed SK data. - `event_type`: (`all`, `sr`, `mr`) - `all`: All events that pass the selection criteria. - `sr`: Single-ring events only. - `mr`: Multi-ring events only. - `x_bin_id`: Bin ID to match between data observations and model predictions. - `x_bin_center`: Mean value of visible energy for events in the x bin. - `y_nmult_est`: Average estimated neutron multiplicity for events in the x bin. Data includes estimated y errors: - `yerr_total`: Total uncertainty for the observed `y_nmult_est`, calculated as the L2 norm of the following uncertainty components. - `yerr_stat`: Statistical uncertainty. - `yerr_effscale`: Systematic uncertainty due to uncertainty in neutron signal efficiency scale (assumed to be fully correlated across all bins) - `yerr_other`: Other systematic uncertainties (assumed to be independent and uncorrelated across bins) 3. `model_predictions.csv`:Contains various model predictions for comparison with the observed data. - `fsi_model`: FSI model used within neutrino event generators: (`"neut_5.4.0"`, `"neut_5.6.3"`, `"genie_ha"`, `"genie_hn"`, `"genie_bert"`, `"genie_incl"`) - `sec_model`: Secondary hadron-nucleus interaction model used within detector simulators: (`"sk45_default"`, `"sk6_default"`, `"g3_gcalor"`, `"g4_bert"`, `"g4_bert_pc"`, `"g4_incl_pc"`) ---
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.057 | 0.047 |
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".