Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
article Share on IEEE-CS/ACM computing curricula: computer engineering & software engineering volumes Authors: John Impagliazzo Hofstra University, Hempstead, NY Hofstra University, Hempstead, NYView Profile , Esther A. Hughes Virginia Commonwealth University, Richmond, VA Virginia Commonwealth University, Richmond, VAView Profile , Richard LeBlanc Georgia Tech, Atlanta, GA Georgia Tech, Atlanta, GAView Profile , Tim Lethbridge University of Ottawa, Ottawa, Ontario, Canada University of Ottawa, Ottawa, Ontario, CanadaView Profile , Andrew McGettrick University of Strathclyde, Glasgow, United Kingdom University of Strathclyde, Glasgow, United KingdomView Profile , Ann E. K. Sobel Miami University, Oxford, OH Miami University, Oxford, OHView Profile , Pradip K. Srimani Clemson University, Clemson, SC Clemson University, Clemson, SCView Profile , Mitchell D. Theys University of Illinois at Chicago, Chicago, IL University of Illinois at Chicago, Chicago, ILView Profile Authors Info & Claims ACM SIGCSE BulletinVolume 36Issue 1March 2004 pp 450–452https://doi.org/10.1145/1028174.971453Published:01 March 2004Publication History 0citation798DownloadsMetricsTotal Citations0Total Downloads798Last 12 Months4Last 6 weeks1 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.006 |
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