TO THE 80TH ANNIVERSARY OF THE LIBERATION OF KALININ. RECOGNITION OF THE DEAD 81 SOLDIERS 243 SD ACCORDING TO THE SPATIO-TEMPORAL DATA OF ARCHIVAL DOCUMENTS
Bibliographic record
Abstract
Представлены результаты практической апробации предложенной методики подготовки обоснования для признания погибшими воинов, пропавших без вести. Методика основывается на использовании ГИС с архивными и современными картами, а также архивных материалов из базы данных системы «Память народа» и Центрального архива Министерства обороны. Около четверти из общего числа воинов, признанных погибшими, воевала в 243 сд[54], которая вела оборонительные и наступательные бои в 1941-1942 гг. в районе г. Ржев и г. Калинин. The results of the practical approbation of the proposed methodology for the preparation of a justification for the recognition of dead missing soldiers are presented. The methodology is based on the use of GIS with archival and modern maps, as well as archival materials from the database of the system "Memory of the People" and the Central Archive of the Ministry of Defense. About a quarter of the soldiers recognized as dead fought in 243 sd, which conducted defensive and offensive battles in 1941-1942 in the area of Rzhev and Kalinin.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".