Investigations at the Heereskraftfahrpark (HKP) 562 Forced-Labor Camp in Vilnius, Lithuania
Bibliographic record
Abstract
This research, examining the site of the HKP Forced-Labor Camp in Vilnius, Lithuania, located and better defined the characteristics and remaining features of the 1944 camp. There were four over-arching objectives for this research. First, to find the entrance into the principal hiding place where Jews interned in the camp took refuge just before the camp’s liquidation by the Nazis and their local collaborators. Next, find the location of the burial trench(es) where Jewish prisoners who were found in hiding were murdered and initially buried. Next, to find the mass-burial site where Jewish survivors reburied the remains from the trench(es). Lastly, to locate any other evidence related to the murder of Jews at the HKP 562 site. Ground-Penetrating Radar (GPR) found the principal hiding place in the basement of Building 2. Electrical Resistivity Tomography (ERT) discovered the two trenches where camp inhabitants who were shot on-site during liquidation were first buried. ERT also found the location of the mass grave that holds the reburied remains from the trenches. Bullet-scarred walls near the burial trenches indicate where the Jews were shot on-site. This research solved one of the thousands of unknowns about the Holocaust, using geoscience to uncover forgotten and hidden history. The materials and methodologies used in this research can be applied in uncovering this history at thousands of other Holocaust and genocide sites worldwide.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".