Summary of the 19th International Conference on Arabidopsis Research (July 23-27, 2008 in Montreal, Canada)
Bibliographic record
Abstract
The 19th International Conference on Arabidopsis Research was a successful meeting attended by 815 scientists from around the world including 322 from the United States, 146 attendees from Canada, 179 from Europe, 134 from Asia, and 34 from a combination of Australia, South America, Africa and the Middle East. The scientific program was of excellent quality featuring 64 talks, including 41 from invited speakers. The Keynote Lecture, delivered by Chris Somerville (Energy Biosciences Institute/UC Berkeley) was particularly relevant to US agriculture and energy research and was titled The Development of Cellulosic Biofuels. There were also 6 community-organized workshops featuring 30 additional talks on topics including Frontiers in Plant Systems Biology, Sources and strategies for Gene Structure, Gene Function, and Metabolic Pathway annotation at TAIR and AraCyc, Advanced Bioinformatic Resources for Arabidopsis, Laser Microtechniques and Applications with Arabidopsis, Plant Proteomics- Tools, Approaches, Standards and Breakthroughs in Studying the Proteome, and Phytohormone Biosynthesis and Signal Transduction. Conference organizers arranged a special seminar by Jim Collins (head of the Directorate of Biosciences at NSF) to provide a community discussion forum regarding the future of Arabidopsis research. Approximately 575 posters were presented in topic areas including, among others, Development, Signal Transduction, Cell Walls, Non-Arabidopsis Systems, and Interactions with Biotic and Abiotic Factors. All conference abstracts and the full program are posted at The Arabidopsis Information Resource (TAIR), a publicly-accessibly website (www.arabidopsis.org/news/abstracts.jsp.) A survey completed by approximately 40% of the meeting attendees showed high satisfaction with the quality of the presentations, meeting organization and the city of Montreal. The conference is the largest annual international Arabidopsis venue which allowed the exchange of information at the forefront of Arabidopsis research and facilitated the establishment of new, and the strengthening of old, collaborations and networks. In addition, the conference provides the site for the annual meetings of the Multinational Arabidopsis Steering Committee (MASC) and the North American Arabidopsis Steering Committee (NAASC.) Graduate students, postdoctoral researchers, junior faculty, and underrepresented minorities made up half of the oral presentations thereby promoting the training of young scientists and facilitating important career development opportunities for speakers. Several poster sessions provided an opportunity for younger participants to freely meet with more established scientists. The NAASC continued its outreach efforts and again sponsored two special luncheons to encourage personal and professional development of young scientists and underrepresented minorities. The Emerging Scientists Luncheon featured 8 graduate students selected on the basis of scientific excellence of their submitted research abstracts. Also attending were the Keynote Speaker and faculty conference organizers. The Minority Funding Luncheon, featured 7 awardees (2 female graduate students, 2 female faculty, 2 male graduate students and 1 male faculty) selected by the NAASC through a widely-publicized application process. This luncheon was established specifically to provide an opportunity for underrepresented minorities, and/or scientists from Minority-Serving Institutions/Historically Black Colleges and Universities to network with NAASC members and representatives from federal funding agencies in an informal and intimate setting. This luncheon included introductions of each award recipient and discussion of outreach efforts and informal research and career discussions. Staff members from The Arabidopsis Information Resource (TAIR), the public U.S. Arabidopsis bioinformatics resource, led one workshop and participated in another to convey information to the community about Arabidopsis resources. Participation by young researchers was facilitated through DOE-sponsored registration awards to 10 early career applicants from the US including five graduate students, four postdoctoral scholars and one new assistant faculty member.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.382 | 0.219 |
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".