Combinatorial and geometric group theory : Dortmund and Ottawa-Montreal Conferences
Bibliographic record
Abstract
Preface.- Subgroups of small index in the automorphism groups of free groups and Kazhdan's (T) property.- Dynamics of free group automorphisms.- Geodesic rewriting systems and pregroups.- Reglar sets and counting in free groups.- Twisted conjugacy for virtually cyclic groups and crystallographic groups.- Solving random equations in Garside groups using length functions.- An application of word combinatorics to decision problems in group theory.- Equations and fully residually-free groups.- The F_n-action on the product of the two limit trees for an iwip automorphism.- Mather invariants in groups of piecewise-linear homeomorphisms.- Algebraic geometry over the additive monoid of natural numbers. Systems of coefficient-free equations.- Some graphs related to Thomson's group F.- Generating tuples of virtually free groups.- Limits of (Thompson's) group F.-
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.134 | 0.034 |
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".