GECCO '09: Proceedings of the 11th annual conference on Genetic and evolutionary computation
Bibliographic record
Abstract
These proceedings contain the papers presented at the 11th Annual Genetic and Evolutionary Computation Conference (GECCO-2009), held in Montreal, Canada, July 8-12, 2009. After 2007, when GECCO was held in London, UK, this is the second time GECCO has been held outside the U.S. The generally high number of submissions of previous events has been maintained: 531 papers have been submitted for review, which is an increase of about 18percent when compared to last year. Of these 531 papers, 220 were accepted as eight-page publications and 25 minutes presentations at the conference, yielding an acceptance ratio of 41,4percent. In addition, 137 submissions (25,8percent) have been accepted for poster presentations with two-page abstracts included in the proceedings. Last year, GECCO successfully moved over to electronic proceedings, and we continued with this publishing strategy as it greatly facilitates the handling of all conference materials. GECCO has lived up to its motto of one conference, many mini-conferences. This year, there were 15 separate tracks that operated independently from each other. Each track had its own track chair(s) and individual program committee. A member of one track's program committee was not allowed to simultaneously be a member of another track's committee. To reduce any bias reviewers might have, all reviews were conducted double blind, no authors' names were included in the reviewed papers. About 600 researchers participated in the reviewing process. We want to thank them for all their work, which is highly appreciated and absolutely vital for the quality of 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 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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.043 | 0.013 |
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".