The New Millennium for CCGA - Beyond 2000 I/O
Bibliographic record
Abstract
ABSTRACT The ceramic column grid array (CCGA) package is used today for an increasing number of microelectronic products due to its many advantages: interconnection density; number of interconnections, compatibility with standard surface mount technology (SMT) assembly techniques; and excellent thermal and electrical performance. CCGA packages are commonly used for logic and microprocessor applications and can be found in a variety of systems including work station, server and network applications. As interest in CCGA packaging has increased, so have the challenges in meeting the interconnection and system application requirements. Increasing numbers of interconnects are required for network applications. The 1657 I/O provided on a 42.5 mm, 1.0 mm pitch CCGA are no longer sufficient for new applications. The industry is driving to more than 1500 signals for these I/O intensive applications, resulting in over 2000 total connections. Manufacturability constraints limit the cost effectiveness of the printed circuit board (PCB) to 1.0 mm pitch packages for high interconnection applications. Thus, increasing the body size while maintaining 1.0 mm pitch is preferred over decreasing the pitch to 0.8 mm and maintaining the body size at 42.5 mm.
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 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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.040 | 0.015 |
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".