Proceedings of the 5th ACM SIGPLAN international conference on Principles and practice of declaritive programming
Bibliographic record
Abstract
The Fifth ACM-SIGPLAN International Conference on Principles and Practice of Declarative Programming (PPDP 2003) was held as part of the federated conference titled Principles, Logics, and Implementations of high-level programming languages (PLI 2003). Other meetings held during PLI 2003 were the 8th ACM SIGPLAN International Conference on Functional Programming (ICFP 2003), the International Symposium on Logic-based Program Synthesis and Transformation (LOPSTR 2003), the Workshop on Declarative Programming in the Context of OO Languages (DP-COOL'03), the Workshop on Mechanized Reasoning about Languages with Variable Binding (MERLIN 2003), the 2003 Haskell Workshop, and the 2003 Erlang Workshop. These events are organized by SIGPLAN, ACM's Special Interest Group on Programming Languages. Previous PLI meetings were held in Paris (September 1999), Montreal (September 2000), Firenze (September 2001), and Pittsburgh (October 2002).PPDP aims to stimulate research in the use of logical formalisms and methods for analyzing, specifying, and performing computations. Of general interest to this meeting are all aspects surrounding declarative programming languages such as logic programming, functional logic programming, and constraint programming. Topics of more specific interest are enhancements to such formalisms with mechanisms for concurrency, mobility, modularity, object-orientation, and static analysis, as well as the fuller exploitation of the programming-as-proof-search framework through new designs and improved implementation methods. At the level of methodology, PPDP welcomes papers on the use of logic based principles in the design of tools for program development, analysis, and verification relative to all programming paradigms.A total of 48 submissions were received in response to the call for papers. The CyberChair conference management system was used to handle submissions and the electronic program committee meeting. Each paper was reviewed by at least three referees and 24 papers were accepted for publication in these proceedings. In addition to the selected presentations, the scientific program contained invited talks by Bruno Blanchet (Max Planck Institut fur Informatik, Saarbrucken) and Mogens Nielsen (BRICS, University of Aarhus), as well as a joint PPDP-ICFP invited talk by Mitchell Wand (Northeastern University, Boston).
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.008 |
| Insufficient payload (model declined to judge) | 0.109 | 0.037 |
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".