Proceedings of the 38th International Symposium on Symbolic and Algebraic Computation
Bibliographic record
Abstract
The 2013 International Symposium on Symbolic and Algebraic Computation (ISSAC) is the premier conference for research in symbolic computation and computer algebra. ISSAC 2013, held at Northeastern University in Boston, USA, is the 38th meeting in the series, which began in 1966 with the seminal ACM Symposium on Symbolic and Algebraic Manipulation. ISSAC 2013 is fully sponsored by the Association for Computing Machinery and its Special Interest Group on Symbolic Manipulation (ACM SIGSAM). The ISSAC meeting is a showcase for original research contributions on all aspects of computer algebra and symbolic mathematical computation, including: Algorithmic aspects: Exact and symbolic linear, polynomial and differential algebra Symbolic-numeric, homotopy, perturbation and series methods Computational algebraic geometry, group theory and number theory Computer arithmetic Summation, recurrence equations, integration, solution of ODEs and PDEs Symbolic methods in other areas of pure and applied mathematics Complexity of algebraic algorithms and algebraic complexity Software aspects: Design of symbolic computation packages and systems Language design and type systems for symbolic computation Data representation Considerations for modern hardware Algorithm implementation and performance tuning Mathematical user interfaces Application aspects: Applications that stretch the current limits of computer algebra algorithms or systems, use computer algebra in new areas or new ways, or apply it in situations with broad impact. The ISSAC Program Committee adhered to the highest standards and practices in the evaluation of submitted papers, and we are very pleased with the quality of the papers appearing at the conference. All papers submitted to ISSAC were judged, and accepted or rejected, solely according to their scientific novelty and excellence. An average of more than 3.3 referee reports were obtained for each submission, and 47 papers were ultimately accepted for publication. Each submitted paper was assigned to two Program Committee members, but all members could and did actively participate in the evaluation of other papers. Strict conflict of interest rules were enforced, disallowing any access to the evaluation process of papers by institutional colleagues, recent co-authors, supervisors, students or under any other biasing circumstance. All papers for which broad agreement was not obtained were voted upon in a final and binding ballot. The Program Committee thanks all the authors of all submitted papers for considering ISSAC for their best work, and hopes that the high quality of the accepted papers validates their choice of venues and encourages submission to ISSAC in the future. ACM SIGSAM sponsors awards for Distinguished Papers and Distinguished Student Authors at every ISSAC, and these will be selected by a vote of the Program Committee. While the winners are not known at the time of this writing, the quality of the candidates ensures that these papers should have great merit and impact on our field. ISSAC features invited talks, contributed papers, tutorials, posters and software demonstrations. These Proceedings contain all accepted contributed papers, and abstracts of the invited talks and tutorials. Abstracts of posters and software demonstrations will appear in an upcoming issue of the ACM SIGSAM Communications in Computer Algebra. We are thrilled with the exceptional scientific stature of our invited presenters, and the high quality of all the contributed works, and thank everyone for their investment in ISSAC 2013.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.116 | 0.048 |
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".