Development of Java GAMUT (JGAMUT) – Adopted Levels, Gammas Evaluator Assistant Code
Bibliographic record
Abstract
The Java GAMUT (JGAMUT) code is designed to be a tool which assists evaluators in producing Adopted Levels, Gammas (ALG) datasets.In particular JGAMUT reduces the amount of tedious work performed by the evaluator; provides routines for systematically correcting discrepant data, which previously was done inconsistently between evaluators; provides more sophisticated statistical methods for obtaining adopted gamma-ray energies and intensities.This code includes a gamma-by-gamma routine, which essentially automates the weighted averaging process originally done by evaluators by hand, as well as the GAMUT routines which use the algorithms of the original GAMUT code to produce more statistically sound adopted energies and intensities.Details regarding the algorithms and usage of this code are contained in this document for the reference of the users.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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 teacher head, 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".