Proceedings of the 7th ACM conference on Electronic commerce
Bibliographic record
Abstract
The papers in these proceedings represent the technical contributions to the 7th ACM Conference on Electronic Commerce -- EC'06, held June 11-15, 2006, at the University of Michigan in Ann Arbor, Michigan, USA. Since its inception in 1999, ACM EC has served as the leading scientific conference on advances in theory, systems, and applications for electronic commerce. The natural focus of the conference is on computer science issues, but the conference is interdisciplinary in nature, addressing a number of facets of electronic commerce including (1) theory and foundations; (2) languages; (3) automation, personalization, and targeting; (4) security, privacy, encryption, and digital rights; (5) applications and empirical studies; and (6) social factors. In addition to the main technical program, EC'06 featured four workshops, four tutorials, and invited keynote presentations from UC Berkeley School of Information Professor Hal Varian and Harvard Economics Professor Drew Fudenberg.The call for papers attracted 127 submissions from authors in academia and industry from around the world, including Africa, Asia, Canada, Europe, the Middle East, and the United States. Each paper was reviewed by at least three program committee members on the basis of scientific novelty, technical quality, and importance to the field. After discussion and deliberation among the program committee and program chairs, 36 papers were selected for publication in these proceedings and for presentation at the conference.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".