Bibliographic record
Abstract
Solutions were prepared from CRM standards and further diluted with nitric acid and distilled water. Samples were placed in polyethylene vials before transport to an inner SLOWPOKE-2 irradiation site where they were exposed to a predominately thermal neutron flux for 60 s. After irradiation the samples were sent to an array of 3He detectors which recorded the DN emissions as a function of count time up to 3 minutes. Further details regarding the delayed neutron counting system and these measurements can be found in references 1 and 2 respectively. Experimental data has been corrected for dead time effects and neutron background contributions [3]. Measurements have been normalized by fissile mass [g] and detection efficiency (33 %) to obtain DN emission rate, Q(t) [s-1g-1]. Each isotope (233U, 235U and 239Pu) was irradiated and counted in triplicate, the provided measurements represent their average Q(t). 2. MCNP Simulations Atomic Energy of Canada Limited has provided a MCNP input deck containing LEU SLOWPOKE-2 dimension and material specifications, the contents of which are detailed in Ref. 4. This input deck was modified to include a polyethylene vial within an inner irradiation site to determine a higher fidelity neutron flux spectrum. This flux was recreated within the vial solution of a second input deck, which includes the irradiation of a fissile solution for 60 s and the recording of subsequent DN emissions from the vial. The DN emission Rate, Q(t) [s-1g-1] was compared to the normalized measurements described in the previous section. The final deck simulated energy deposition within the 3He detectors, Figure 4. MCNP6v1 was used in the following simulations (load date: 05/08/13).
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.096 | 0.072 |
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".