Bibliographic record
Abstract
文中建立了一种对准循环低密度奇偶校验码的环路的几何描述方法,并在此基础上提出了一种准循环低密度奇偶校验码的构造方法. 该算法顺序地选择每个循环置换矩阵,通过保证当前循环置换矩阵与已经构造的循环置换矩阵之间不形成长度小于<italic>g</italic>的环路,从而完成对最小环长为<italic>g</italic>的准循环低密度奇偶校验码的构造.与采用随机构造法构造最小环长为<italic>g</italic>的准循环低密度奇偶校验码相比,该算法大大降低了构造的复杂度.仿真结果表明,采用文中所提出的构造方案构造的准循环低密度奇偶校验码, 其误码性能在分组长度为中等以下时不仅优于传统的随机码,并且优于基于有限几何的低密度奇偶校验码.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.004 |
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; both teacher heads agree on what is shown here.
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".