Final CRADA Report: Accelerated Burn-up Accumulation Test of Clean Core Thorium Energy Designated ANEEL Fuel
Bibliographic record
Abstract
Clean Core Thorium Energy (CCTE), LLC, located in Oak Brook, Illinois, is committed to the development of alternative nuclear fuels. CCTE is focused on leveraging the inherent benefits of thorium to create a novel nuclear fuel solution for our worlds growing power demand. Unlike some other fuel cycles proposing to use thorium in advanced reactors, CCTE is focused on deploying solid fuel designs (ceramic pellets in metallic cladding) in existing pressurized heavy-water reactors (PHWRs) and Canada deuterium uranium (CANDU) reactors. CCTE’s fuel design, referred to as Advanced Nuclear Energy for Enriched Life (ANEEL), uses mixed thorium-uranium oxide ((Th,U)O2) to enhance reactor operational strategies while producing significantly low attractiveness material in terms of nuclear proliferation. The overall project objective is to investigate the performance of high burnup ANEEL fuel via an irradiation experiment to be performed in the Advanced Test Reactor (ATR) at the Idaho National Laboratory (INL). The scope of work for this CRADA was specifically aimed at performing conceptual design and analysis to support development of an irradiation test rig, development of a fuel fabrication process for the experiment pellets, fabrication and qualification of the pellets, and shipment of the pellets to INL so they can be used to construct experiment rodlets.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".