Collaborative Research: North East Cyberinfrastructure Consortium
Bibliographic record
Abstract
EPS-0918284, University of Vermont & State Agricultural College, J. L. Van Houten, linked to EPS-0918033 (University of New Hampshire), EPS-0918078 (University of Delaware), EPS-0918018 (University of Maine), EPS-0918061 (University of Rhode Island) Collaborative Research: North East Cyberinfrastructure Consortium This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). The North East Cyberinfrastructure Consortium (NECC) unites Maine (ME), New Hampshire (NH), Vermont (VT), Rhode Island (RI), and Delaware (DE) to support cyber-enabled research that requires analyses of large datasets. The project is organized around sharing resources, expertise and facilities in order to make cyber-enabled collaborative research possible in a sparsely populated region and among non-contiguous states. Intellectual Merit. The consortium has three primary needs to support regional, cyber-enabled research: 1) long-term leases on fiber in specific reaches across the northeast to provide high-speed connectivity with dense-wave division capability; 2) redundant, distributed Data Centers for regional cyber-enabled collaborations; and 3) cyber-knowledgeable personnel to allow researchers to access regional compute, analysis and visualization resources. Much of the physical infrastructure required for the NECC network exists, but there are four key reaches of fiber needed in ME, NH, RI and VT. In ME, two stretches are required to provide a redundant route for national and international connectivity through CANARIE (Canada's advanced network organization) and along the I-95 corridor. A fiber route along the I-89 corridor provides connectivity to Boston for Vermont and New Hampshire to Boston. The researchers have been working with the Northeast Research and Education Network (NEREN) to manage the fiber network once it is in place. Broader Impacts. The possibility of a fiber network that would provide adequate bandwidth for videoconferencing has led to the NECC regional organization around outreach programs for STEM workforce development and diversity. It is planned to create a new Watershed Project through partnerships among multiple state-based programs for high school and undergraduate students. Students in this project from all the NECC states, NY and Puerto Rico, who otherwise would not even meet, will work together in collaborative watershed research. Following training, teams of high school students and teachers or undergraduates join with state programs to work on watershed science during the summer or through the summer and the academic year. The individual NECC state programs are effective in improving participation in STEM majors and diversity, but with the new fiber network and the ability to communicate over the new cybernetwork, a larger, region-wide effective program, with emphasis on cyber-based communication and research tools, is envisioned. The researchers develop a multi-faceted communication plan that will spread the word about the importance of the cyber-enabled research to the public through innovative television shows, podcasts and educational materials. An Ambassador Program will partner with citizen science groups to inform the public about the importance of a fiber network to education and science and about the potential impact of the cyber-enabled metagenomics study to the economies of the states. The fiber network will have an enormous economic impact on the region. The pilot project on metagenomics of the bacterial communities in blooms in lakes in VT, NH, ME and RI will contribute to the understanding of the origin of these blooms and their toxins that shut down access to recreational and drinking water sources. Lakes in the northeast are extremely important to economies, with estimates of $1.5B in lake-related revenues to NY, VT and Quebec each year from Lake Champlain; $2B annually from lake recreational revenues to Maine; 14,000 jobs and bring in $1.8B in revenues from boating, fishing, swimming, drinking water and property taxes to New Hampshire.
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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 | 0.012 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.259 | 0.157 |
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".