This repository offers a promising solution to identify fraudulent manuscripts, and it could be a valuable tool for supporting scientific integrity. Its code was developed aiming to identify suspect paper mill cases.
Provenance analysis provide a solution to track possible reused and manipulated data. We tested the herein solution in the Stock Photo Paper Mill (SPP) and two extended version of it (SPP-v1) and (SPP-v2).
| Dataset | #Documents | #Figures | #Panels |
|---|---|---|---|
| SPP | 121 | 498 | 2581 |
| Extended SPP (v1) | 1090 | 1467 | 10143 |
| Extended SPP (v2) | 4725 | 5303 | 47540 |
Code and instructions to use our method are released at provenance directory.
Panel extraction is essential to focus on the image regions of interest to the scientific integrity problem, and filter out those that might raise false alarms due to their intrinsic similarity (e.g., diagrams, drawings, and legend indicative letters). We collected and annotated 3,836 biomedical scientific figures under creative commons license from different journals, creating a dataset of 3,236 figures (32,507 panels) for training the detector of panels, and 600 figures (4,888 panels) for testing it.
| Class | Images | Labels | P | R | [email protected] | [email protected]:.95: |
|---|---|---|---|---|---|---|
| all | 600 | 4888 | 0.941 | 0.935 | 0.95 | 0.901 |
| Blots | 600 | 804 | 0.998 | 0.989 | 0.995 | 0.871 |
| Graphs | 600 | 1618 | 0.968 | 0.947 | 0.98 | 0.944 |
| Microscopy | 600 | 1838 | 0.955 | 0.934 | 0.941 | 0.922 |
| Body Imaging | 600 | 379 | 0.833 | 0.828 | 0.859 | 0.814 |
| Flow Cytometry | 600 | 249 | 0.948 | 0.976 | 0.973 | 0.953 |
The Panel Extractor README provides instructions to reproduce our results and to download the dataset.
Thought the inhere tool can pinpoint to suspect systematic produced images and documents, its findings cannot be interpreted without the expertise of scientific integrity analysts. If by any chance do you find any suspicious case, please, report it to local integrity organizations.
This work is currently under-review.
João Phillipe Cardenuto, Daniel Moreira, Anderson Rocha et al. Unveiling Scientific Articles from Paper Mills with Provenance Analysis, 03 May 2023, PREPRINT (Version 1) available at Research Square [https://doi.org/10.21203/rs.3.rs-2791141/v1]
@article{Cardenuto2023,
doi = {10.21203/rs.3.rs-2791141/v1},
url = {https://doi.org/10.21203/rs.3.rs-2791141/v1},
year = {2023},
month = may,
publisher = {Research Square Platform {LLC}},
author = {Jo{\~{a}}o Phillipe Cardenuto and Daniel Moreira and Anderson Rocha},
title = {Unveiling Scientific Articles from Paper Mills with Provenance Analysis}
}