Preface: 6th International Conference on Computer Science and Intelligent Communication (CSIC 2024)
Bibliographic record
Abstract
2024 6th International Conference on Computer Science and Intelligent Communication (CSIC 2024) was held in Vancouver, Canada during December 21-22, 2024. This conference provides a forum for accessing to the most up-to-date and authoritative knowledge from both industrial and academic worlds, sharing best practice in the fields of computer science, artificial intelligence, machine learning, information engineering, and communication technology. A key aspect of this conference is the strong mixture of academia and industry. All papers in this proceeding were subject to peer-review by conference committee members and international reviewers. The papers were selected for the proceedings based on quality and relevance to the conference. We express our gratitude to all people who contributed to the review process and did all their best to enhance the scientific merit and quality of the proceedings. We are also grateful to the authors for their contributions, to the speakers and participants. We wish to extend our warmest welcome to all interested participants to the next CSIC. The CSIC Organizing committee Vancouver, Canada
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".