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
ENWEndNote BIBJabRef, Mendeley RISPapers, Reference Manager, RefWorks, Zotero AMA Demczuk S, BiaÅas M, Dyduch G, Drabik G, Chrupek M, OkoÅ K. QUIZ WHAT IS YOUR DIAGNOSIS?. Polish Journal of Pathology. 2013;64(2):160-160. doi:10.5114/pjp.2013.36546. APA Demczuk, S., BiaÅas, M., Dyduch, G., Drabik, G., Chrupek, M., & OkoÅ, K. (2013). QUIZ WHAT IS YOUR DIAGNOSIS?. Polish Journal of Pathology, 64(2), 160-160. https://doi.org/10.5114/pjp.2013.36546 Chicago Demczuk, Sergiusz, Magdalena BiaÅas, Grzegorz Dyduch, Grażyna Drabik, MaÅgorzata Chrupek, and Krzysztof OkoÅ. 2013. "QUIZ WHAT IS YOUR DIAGNOSIS?". Polish Journal of Pathology 64 (2): 160-160. doi:10.5114/pjp.2013.36546. Harvard Demczuk, S., BiaÅas, M., Dyduch, G., Drabik, G., Chrupek, M., and OkoÅ, K. (2013). QUIZ WHAT IS YOUR DIAGNOSIS?. Polish Journal of Pathology, 64(2), pp.160-160. https://doi.org/10.5114/pjp.2013.36546 MLA Demczuk, Sergiusz et al. "QUIZ WHAT IS YOUR DIAGNOSIS?." Polish Journal of Pathology, vol. 64, no. 2, 2013, pp. 160-160. doi:10.5114/pjp.2013.36546. Vancouver Demczuk S, BiaÅas M, Dyduch G, Drabik G, Chrupek M, OkoÅ K. QUIZ WHAT IS YOUR DIAGNOSIS?. Polish Journal of Pathology. 2013;64(2):160-160. doi:10.5114/pjp.2013.36546.
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 | 0.001 |
| Open science | 0.000 | 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