SymCon'04: THE 4TH INTERNATIONAL WORKSHOP \nON SYMMETRY AND CONSTRAINT SATISFACTION PROBLEMS . A Satellite Workshop of CP'2004 (Tenth International Conference on Principles and Practice of Constraint Programming) . 27 September 2004 , Toronto, Canada.
Bibliographic record
Abstract
A symmetry is a transformation of an entity which preserves the properties of the entity. The transformed entity is thus identical to and indistinguishable from the original entity. For instance, rotating a chess board 180 degrees gives us a board which is indistinguishable from the original board. \n \nMany constraint satisfaction problems (CSPs) have symmetries in the variables, domains or constraints - or any combination thereof. Each of these symmetries preserve satisfiability, so that when there is symmetry in a CSP, any assignment can be transformed into an equivalent assignment without affecting whether or not it satisfies the constraints. Similarly, applying such a transformation to a partial assignment does not affect whether or not it can be extended to an assignment satisfying the constraints. For instance, in many CSPs some of the variables refer to entities which are indistinguishable, and the values assigned to these variables can be interchanged in any solution. \n \nSymmetry increases the combinatorial complexity of CSPs. In the presence of symmetry, a constraint solver may waste a large amount of time considering symmetric but equivalent assignments or partial assignments. Hence, dealing with symmetry is often crucial to the success of solving such CSPs efficiently. \n \nAs well as exploiting symmetry when solving CSPs, CSP solving techniques have been used to solve symmetry-related problems. For example, they have been used to answer the question of whether a particular search state is symmetrically equivalent to one already explored. As another example, they have been used to derive "generators" of a symmetry group, which allow the symmetries to be represented effectively without the need to list them all explicitly. Constraint programming techniques have the potential to improve on existing algorithms for solving these and related group-theoretic problems. \n \nThe SymCon'04 workshop will provide a forum for research into any aspect of symmetry and CSPs. It will be the fourth workshop in the series, following the successful earlier workshops SymCon'01 at CP 2001 in Paphos (Cyprus), SymCon'02 at CP 2002 in Ithaca (U.S.A.), and SymCon'03 at CP 2003 in Kinsale (Ireland). \n \nURL: http://zeynep.web.cs.unibo.it/SymCon04/
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.066 | 0.020 |
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".