Bibliographic record
Abstract
No AccessPerspectives on School-Based IssuesArticle1 Apr 2003Language-Reading Resource Model Deborah Lozo and Kathryn Dix Deborah Lozo Cobb County School DistrictMarietta, GA Google Scholar More articles by this author and Kathryn Dix Cobb County School DistrictMarietta, GA Google Scholar More articles by this author https://doi.org/10.1044/sbi4.1.52 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationTrack Citations ShareFacebookTwitterLinked In References Fell-Greene, J. (2000). Language!: Longmont, CO: Sopris West. Google Scholar Georgia Department of Education. (1999). Quality core curriculum and standards. Retrieved February 5, 2003, from www.glc.k12.us Google Scholar Autoskill International. (2001). Academy of reading. Ottawa, Ontario, Canada: Branham Group. Google Scholar Additional Resources FiguresReferencesRelatedDetails Volume 4Issue 1April 2003Pages: 52-54 Get Permissions Add to your Mendeley library History Published in issue: Apr 1, 2003 Metrics Topicsasha-topicsleader-topicsasha-article-typesasha-sigsCopyright & PermissionsCopyright © 2003 American Speech-Language-Hearing AssociationLoading ...
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.010 | 0.027 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.084 | 0.027 |
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".