Computing the real solutions of polynomial systems with the RegularChains library in Maple
Why this work is in the frame
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Bibliographic record
Abstract
demonstration Share on Computing the real solutions of polynomial systems with the RegularChains library in Maple Authors: Changbo Chen University of Western Ontario, Canada University of Western Ontario, CanadaView Profile , James H. Davenport University of Bath, UK University of Bath, UKView Profile , François Lemaire Université de Lille 1, France Université de Lille 1, FranceView Profile , Marc Moreno Maza University of Western Ontario, Canada University of Western Ontario, CanadaView Profile , Bican Xia Peking University, China Peking University, ChinaView Profile , Rong Xiao University of Western Ontario, Canada University of Western Ontario, CanadaView Profile , Yuzhen Xie University of Western Ontario, Canada University of Western Ontario, CanadaView Profile Authors Info & Claims ACM Communications in Computer AlgebraVolume 45Issue 3/4September/December 2011 pp 166–168https://doi.org/10.1145/2110170.2110174Online:23 January 2012Publication History 5citation95DownloadsMetricsTotal Citations5Total Downloads95Last 12 Months3Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it