Research on the Deep Development of Military and Civilian Integration in Mianyang Technological City
Bibliographic record
Abstract
The party after the 19th held large in China, China has entered a new era, from the domestic and international pattern, the depth of the development of military and civilian integration national strategy is the requirement of the new era, also is the construction of “Chinese dream” the only way. Combined with the related policy and this background, in Mianyang sci-tech city, for example, on the current policy of Mianyang city system, special achievements, series platform, and experience system review and summary, the civil-military integration has made some progress and summary and analysis on the current situation, the civil-military integration problem consciousness, innovation mechanism, the industrial mechanism, talent incentive, financial services, cooperation, open content such as research, and according to the problems to study and put forward solutions or Suggestions. The scientific research to provide good atmosphere to Mianyang related personnel training, provide a reference for improving the relevant military and civilian integration system, for Mianyang, similar or related areas of military and civilian integration development provide reference and reference of experience, rich civil-military integration of theory and practice in our country, promote the development of China’s military and civilian integration to a higher level and wider platform.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".