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
A simple mathematical model of the scientific peer reviewing process is developed. Papers and reviewers are modeled as numerical vectors, respectively representing the paper’s value among multiple quality dimensions, and the importance given to these dimensions by a given reviewer. Computer simulations show that the model can reproduce various characteristics of a real-world paper decision process, and in particular its propensity to act as an “arbitrary” decision procedure for a range of submissions. A key finding of this study is that the appearance of randomness can be explained by a mismatch between high quality dimensions of a paper, and those valued by the reviewers it is assigned to. As a consequence, a program committee may exhibit arbitrariness even with a set of completely reliable reviewers. Various factors contributing to this arbitrariness are then examined, and alternate selection models are studied that could help reduce arbitrariness and reviewer effort.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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