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Record W7072343729

Workshop and conference on Grand Challenges applications and software technology

2010· other· en· W7072343729 on OpenAlexfundno aff

Bibliographic record

VenueOSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2010
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicAquatic life and conservation
Canadian institutionsnot available
FundersLos Alamos National LaboratoryOak Ridge National LaboratoryLawrence Livermore National LaboratoryUniversity of California, Santa BarbaraAdvanced Research Projects AgencyGoddard Space Flight CenterAmes Research CenterNational Oceanic and Atmospheric AdministrationDefense Advanced Research Projects AgencyVanderbilt UniversityRice UniversityNational Institute of Standards and TechnologyCarnegie Mellon UniversityArgonne National LaboratoryInternational Business Machines CorporationU.S. Department of EnergyCalifornia Institute of TechnologyLangley Research CenterNational Aeronautics and Space AdministrationUniversity of MinnesotaYork UniversityNASA HeadquartersNational Science Foundation
KeywordsGrand ChallengesSoftwareMultidisciplinary approachGovernment (linguistics)National laboratoryCyberinfrastructureComputational thinking
DOInot available

Abstract

fetched live from OpenAlex

On May 4--7, 1993, nine federal agencies sponsored a four-day meeting on Grand Challenge applications and software technology. The objective was to bring High-Performance Computing and Communications (HPCC) Grand Challenge applications research groups supported under the federal HPCC program together with HPCC software technologists to: discuss multidisciplinary computational science research issues and approaches, identify major technology challenges facing users and providers, and refine software technology requirements for Grand Challenge applications research. The first day and a half focused on applications. Presentations were given by speakers from universities, national laboratories, and government agencies actively involved in Grand Challenge research. Five areas of research were covered: environmental and earth sciences; computational physics; computational biology, chemistry, and materials sciences; computational fluid and plasma dynamics; and applications of artificial intelligence. The next day and a half was spent in working groups in which the applications researchers were joined by software technologists. Nine breakout sessions took place: I/0, Data, and File Systems; Parallel Programming Paradigms; Performance Characterization and Evaluation of Massively Parallel Processing Applications; Program Development Tools; Building Multidisciplinary Applications; Algorithm and Libraries I; Algorithms and Libraries II; Graphics and Visualization; and National HPCC Infrastructure.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.952
Threshold uncertainty score0.335

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.227
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueOSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)Same topicAquatic life and conservationFrench-language works237,207