International Registered Reports Identifiers (IRRIDs): 7 Years of Experiences
Bibliographic record
Abstract
Gunther Eysenbach1 Objective Registered Reports (RRs) refer to the publication of a study that is published in 2 stages: a protocol (RR stage 1 or RR1) and a results paper (RR2). Some journals have adopted the RR system and guarantee acceptance of subsequent results articles published in the same journal after the protocol is peer reviewed. However, in a distributed open science ecosystem, protocols may already be peer reviewed and published elsewhere, but no standardized system exists to link protocols to subsequent results articles and vice versa. We implemented RRs across the publisher portfolio, with 1 dedicated journal to peer review and publish protocols, and the publisher guaranteeing acceptance of RR2s in 1 of its other journals independently based on whether the results were negative or positive. We propose a machine- and human-readable mechanism to link RR2s with RR1s to assist in peer review and to enhance transparency, accountability, and reproducibility. Design In 2018, we proposed and implemented a cross-journal, DOI-based, persistent identifier called an International Registered Report Identifier (IRRID) published in article abstracts. An RR2 references an RR1 using an identifier that is based on the DOI of the protocol. For example, RR2-10.2196/24264 indicates that the publication is a results article for a protocol that was previously published under the DOI 10.2196/24264.1 Protocols that are peer reviewed contain the IRRIDs in the format [DE|P]RR1-[DOI], where [DOI] is the DOI of the protocol itself, and DE or P qualifiers indicate whether the protocol was written before [P] or after [DE] data collection. On submission of a protocol, authors were asked if the protocol was submitted before or after data were collected. Authors were incentivized to register their protocol by being offered a 20% discount on the Article Processing Charge on subsequent results articles. Results A total of 3995 articles were published with IRRIDs between 2018 and February 13, 2025, of which 3240 (81%) were protocols (RR1). Among the protocols, 2151 (66%) were published when data already existed (DERR1), and 917 (28%) were published before data were collected (PRR1). A total of 732 results articles had an RR2 identifier indicating previous protocol publication, although these protocols were not always peer reviewed (eg, OSF or BMJ Open). A third-party audit found that outcome switching and undeclared deviations from the protocol still remain a problem.2 Conclusions We propose that other journals adopt IRRIDs to help identify protocol and results article pairs that together form RRs across journals (https://irridregistry.org/). References 1. What is an International Registered Report Identifier (IRRID)? JMIR Publications Knowledge Base and Help Center. Accessed February 13, 2025. https://support.jmir.org/hc/en-us/articles/360003797672-What-is-an-International-Registered-Report-Identifier-IRRID 2. Anthony N, Tisseaux A, Naudet F. Published registered reports are rare, limited to one journal group, and inadequate for randomized controlled trials in the clinical field. J Clin Epidemiol. 2023;160:61-70. doi:10.1016/j.jclinepi.2023.05.016 1JMIR Publications, Toronto ON, Canada, geysenba@gmail.com. Conflict of Interest Disclosure Gunther Eysenbach has an equity stake in and receives a salary from JMIR Publications.
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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 | 0.074 | 0.158 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.017 | 0.024 |
| Open science | 0.004 | 0.016 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.085 | 0.064 |
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".