Bibliographic record
Abstract
ABSTRACT Conference proceedings are one of the most important forms of communication for computer scientists. This study investigated the policies of a large number of computer science journals with regard to the republication of papers which had already appeared in conference proceedings. Nearly one‐quarter of journal editors would not republish such papers other than in special circumstances (such as a special conference issue), and almost all of the remainder would do so only after substantial updating and expansion of the original paper. Many specified the amount of content that should be new: 30% was the proportion most frequently mentioned. Thus, many sections of text may be identical to the original paper. However, some journal editors do not appear to consider this self‐plagiarism provided the original publication is properly cited. Nevertheless, such (re)publication is likely to lead to high similarity scores in CrossCheck; in this field, therefore, journal editors need to exercise particular discretion when evaluating CrossCheck results.
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.
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 | 0.185 | 0.644 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.016 | 0.023 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.021 | 0.016 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.038 | 0.013 |
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".