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
Lókös István: Lectori salutem! 7-8. \nI. Középkor és reneszánsz \nMadarász Imre: Politikai univerzalizmus és nemzeti nyelv a \nDivina Commedia-ban 9-18. \nLőkös István: A Judit és Holofernész-téma a horvát és a magyar reneszánsz \nepikában 19-46. \nKatona Gábor: Philip Sidney poétikájának művészetfilozófiai előzményei 47-62. \nII. Huszadik század \nBerta Erzsébet: Koreszmék és művészetelméleti gondolatok a XX. század \nelső évtizedeiben 63-72. \nBényei Tamás: Egy posztmodern regénytípusról (A detektív és a bűnöző \nmetamorfózisa az antidetektív történetekben) 73-86. \nAbádi Nagy Zoltán: A mai amerikai minimalista próza: kategóriahasználati \nés definíciós helyzetvázlat 87-108. \nMolnár Judit: A québec-i angol nyelvű irodalom helye a kanadai irodalmak \nközött 109-116.
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) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.026 | 0.001 |
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