Bibliographic record
Abstract
All conference organisers/editors are required to declare details about their peer review. Therefore, please provide the following information: • Type of peer review: Double-blind • Conference submission management system: http://submission.iaast.cn/ipec/index.php/public/login The email address used for the management system and the name of the person in charge as follows, Email: contact@ipec2020.org Name: Linda You • Number of submissions received: 682 • Number of submissions sent for review: 513 • Number of submissions accepted: 319 • Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100): 47.0% • Average number of reviews per paper: 2 • Total number of reviewers involved: 164 • Any additional info on review process: • IPEC2021 follows the highest standards of publication ethics and takes all possible procedures against any publication misconduct. This Conference does not accept any type of plagiarism, which means that any author replicating a significant part of another’s work without acknowledging him/her or passing another’s work off as his/her own are not tolerated and not published. • All authors submitting their works to IPEC2021 for publication as original works confirm that the submitted papers are their own contributions and have not been copied in whole or in part from other works. • Each submission is anonymously reviewed by three independent reviewers, to ensure the final high standard and quality of each accepted submission. The IPEC2021 guarantees that the entire peer review and publication process is meticulous and objective. Furthermore, all works not in accordance with these standards will be removed from the publication if malpractice is revealed at any time even after the publication. Every case of suspected plagiarism or duplicate publishing will be reported. • Contact person for queries (please include: name, affiliation, institutional email address) Ms. Caroline Chen Association for Computer, Electronics and Education caroline.chen@canada-acee.org
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 | 0.107 | 0.422 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.028 | 0.010 |
| Open science | 0.010 | 0.009 |
| Research integrity | 0.012 | 0.020 |
| Insufficient payload (model declined to judge) | 0.150 | 0.164 |
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".