Bibliographic record
Abstract
Since October 2001, the development of the facility diagnostics for NIF has been funded by the NIF Director through the National NIF Diagnostic Program (NNDP). The current emphasis of the NNDP is on diagnostics for the early NIF quad scheduled to be available for experiment commissioning in FY03. During the past nine months, the NNDP has set in place processes for funding diagnostics, developing requirements for diagnostics, design reviews, and monthly status reporting. Work has been funded at Lawrence Livermore National Laboratory (LLNL), Los Alamos National Laboratory (LANL), the Naval Research Laboratory (NRL), Sandia National Laboratories (SNL), and Bechtel Nevada at Los Alamos and Santa Barbara. There are no major technical risks with the early diagnostics. The main concerns relate to integration of the diagnostics into the facility; all such issues are being worked. This report is organized to show the schedule and budget status and a summary of Change Control Board actions for the past three months. The following sections then provide short descriptions of the status of each diagnostic. Where design reviews or requirements documents are cited, the documents are available on the Diagnostics file server or on request.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.009 | 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; both teacher heads agree on what is shown here.
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".