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
06–103 Gamliel, Eyal (Ruppin Academic Center, Israel) & Liema Davidovitz, Online versus traditional teaching evaluation: Mode can matter . Assessment & Evaluation in Higher Education (Routledge/Taylor&Francis) 30.6 (2005), 581–592. 06–104 Lorenzo-Dus, Nuria & Paul Meara (U Wales, UK), Examiner support strategies and test-taker vocabulary . International Review of Applied Linguistics in Language Teaching (Mouton de Gruyter) 43.3 (2005), 239–258. 06–105 Luce-Kapler, Rebecca & Don Klinger (Queen's U, Kingston, Canada; rebecca.lucekapler@queensu.ca ). Uneasy writing: The defining moments of high-stakes literacy testing . Assessing Writing (Elsevier) 10.3 (2005), 157–173. 06–106 McClure, James E. (Ball State U, USA) & Lee C. Spector, Plus/minus grading and motivation: An empirical study of student choice and performance . Assessment & Evaluation in Higher Education (Routledge/Taylor&Francis) 30.6 (2005), 571–579. 06–107 Ricketts, Chris (U Portsmouth, UK) & Stan Zakrzewski, A risk-analysis approach to implementing web-based assessment . Assessment & Evaluation in Higher Education (Routledge/Taylor&Francis) 30.6 (2005), 603–620.
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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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