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
The Concise Data Processing Assessment (CDPA) was developed to probe student abilities related to the nature of measurement and uncertainty and to handling data. The diagnostic is a ten question, multiple-choice test that can be used as both a pre-test and post-test. A key component of the development process was interviews with students, which were used to both uncover common modes of student thinking and validate item wording. To evaluate the reliability and discriminatory power of this diagnostic, we performed statistical tests focusing on both item analysis (item difficulty index, item discrimination index, and point-biserial coefficient) and on the entire test (test reliability and Ferguson's delta). Scores on the CDPA range from chance (for novices) to about 80% (for experts), indicating that it possesses good dynamic range. Overall, the results indicate that the CDPA is a reliable assessment tool for measuring targeted abilities in undergraduate physics students.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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