Proceedings of the 6th ACM SIGPLAN international conference on Principles and practice of declarative programming
Bibliographic record
Abstract
This volume consists of the refereed papers presented at the 6th ACM-SIGPLAN International Conference on Principles and Practice of Declarative Programming, held in Verona, Italy, August 24-26, 2004. PPDP'04 is the sixth in this series of international meetings on declarative programming. The previous meetings were held in Uppsala, Sweden in 2003, Pittsburgh, USA in 2002, Firenze, Italy in 2001, Montreal, Canada in 2000, and Paris, France in 1999.The goal of the PPDP conferences is to present research on the use of declarative methods in programming and on the design, implementation and application of programming languages that support such methods. The emphasis is on ideas that transcend the boundaries of any one declarative formalism, thus being of interest to those working in any declarative paradigm.44 papers were submitted to the conference. Each paper was reviewed by at least 3 program committee members or their designees. All papers on which there was disagreement had at least 4 readers. After intensive electronic discussion, the Program committee decided to accept 21 papers. In addition to the accepted papers, the conference included talks by five invited speakers: Sheila McIlraith, Yannis Smaragdakis, Ehud Shapiro, Tom Henzinger, and Greg Morrisett. The invited speakers were shared with other co-located meetings: PEPM 2004 -- Symposium on Partial Evaluation and Program Manipulation, LOPSTR 2004 -- International Symposium on Logic-based Program Synthesis and Transformation, and SAS 2004 -- Static Analysis Symposium.
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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.008 |
| Insufficient payload (model declined to judge) | 0.078 | 0.030 |
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".