Proceedings of the 2006 conference of the Center for Advanced Studies on Collaborative research
Bibliographic record
Abstract
Welcome to CASCON 2007! Each October we gather the foremost thought leaders from around the world together for CASCON, the annual conference on computer science technologies and research, hosted by the IBM Toronto Centre for Advanced Studies. Now, for the seventeenth year, CASCON (CAS Conference) is the showcase event of the year for CAS and the IBM Toronto Lab. With over 1500 attendees, this Meeting of Minds has evolved into a comprehensive forum that addresses questions and developments surrounding technology at large. CASCON, sponsored by the IBM Toronto Lab and CAS, in partnership with the National Research Council Canada is where innovations from the academic, public and industrial sectors converge. While CASCON has grown into an international conference, it is still the key event in Canada where important contacts are made and valuable alliances are formed. This year's conference brings an exciting mix of keynote and Frontiers of Software Practice (FoSP) plenary sessions, papers presentations, workshops, demos, and posters, and promises to be a catalyst for new ideas and collaboration. Each aspect of the conference is a result of the efforts of the many CASCON organizers and all of the participants of CASCON 2007, and we thank them for their time, enthusiasm, and commitment to innovation and collaboration. The 18 full and 12 short papers presented in this year's proceedings were selected from an impressive set of submissions from around the world. The program committee led by co-chairs, Bruce Spencer, of the National Research Council Canada, and Margaret-Anne Storey, of the University of Victoria, spent many hours soliciting high quality papers, ensuring expert reviews of each paper, and making the difficult selection of which papers would be presented at the conference and published in the proceedings. Our thanks to them and to the members of the Program Committee for their diligence and integrity. As with previous years, CASCON proceedings are also available online in the ACM Digital Library http://www.acm.org/ Also included here are the proceedings from the CAS Dublin Software and Systems Engineering Symposium 2007, which occurs on Wednesday, October 24.
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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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.239 | 0.096 |
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".