Bibliographic record
Abstract
The Fuel Test Loop(FTL) which is capable of an irradiation testing under a similar operating condition to those of PWR(Pressurized Water Reactor) and CANDU(CANadian Deuterium Uranium reactor) nuclear power plants has been developed and installed in HANARO, KAERI(Korea Atomic Energy Research Institute). It consists of In-Pile Section(IPS) and Out-of Pile System(OPS). The IPS, which is located inside the pool is divided into 3-parts; the in-pool pipes, the IVA(IPS Vessel Assembly) and the support structures. The test fuel is loaded inside a double wall, inner pressure vessel and outer pressure vessel, to keep the functionality of the reactor coolant pressure boundary. The IVA is manufactured by local company and the functional test and verification were done through pressure drop, vibration, hydraulic and leakage tests. The brazing technique for the instrument lines has been checked for its functionality and performance. An IVA has been manufactured by local technique and have finally tested under high temperature and high pressure. The IVA and piping did not experience leakage, as we have checked the piping, flanges, assembly parts. We have obtained good data during the three cycle test which includes a pressure test, pressure and temperature cycling, and constant temperature.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".