Development of the Shipbuilding Industry of Ukraine in the Postwar Period (1946–1965)
Bibliographic record
Abstract
The article deals with development of the shipbuilding industry of Ukraine in the postwar period (1946–1965). The author determined that in the postwar period the reconstruction of the entire industrial structure was accomplished, the most important works at releasing the shipbuilding plants from their uncharacteristic functions were carried out, the specialization profile in building of watercrafts of different types was worked out, the watercraft typing, unification of master ship engines and supplementary mechanical devices, standardization and normalization of materials and equipment were developed. All that allowed each enterprise to make a speciality of multiple building of one or two types of ships. The problem of technical reconstruction of production also became of great importance in the postwar years. Increasing requirements for the ship technical characteristics caused radical changes in shipbuilding technology. The pace of reconstruction and development of the Ukrainian shipbuilding industry was largely determined by the replenishment of enterprises in the industry by qualified specialists. The author concludes that in the postwar period shipbuilding turned into a highly developed industry and became the most important part of the shipbuilding complex of the USSR. Ukrainian engineering and work force made a decisive contribution to the formation of the Soviet postwar fleet.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".