MétaCan
Menu
Cohort builder

4,299,418 works, Canadian by any of four routes.

Every filter state is a URL; the URL is the query; the query is citable via /q/⟨hash⟩. The page, the API and the export parse the same parameters.

The current cohort, streamed from the database: every work column, the machine labels, the provisional scores, and the per-row validation status. Exports are capped at 100,000 rows. Mints a permanent /q/ link for this exact query. The same filters always produce the same link, whoever asks.

Search term
Author
Year range
Sort
Language
Type
Field
Venue
Topic
Advanced Steganography and Watermarking Techniques
Retraction
Abstract
Evidence source
Study design
Label agreement
Label status

Direct Codex and Gemma labels are unvalidated and sparse. Distilled predictions cover the full frame and are also unvalidated. Choose the evidence source explicitly; absence of a direct label is never a negative label.

affaffiliation
fundfunder
venuejournal
aboutaboutness

The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

654 results · 1 filter active ·
Results by year
20002025
Publication date
Categories
Machine labels · sparse coverage
Evidence
Language
Type
Citations
An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
654 works in the cohort · of 4,299,418page 4 of 14

Labels cover 0 of 654 works in this cohort. The rest are unlabeled, which is not a negative label: the label table is sparse today and grows as labeling rounds land.

Distilled predictions cover 654 of 654 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affno abstractunlabeled
Steganography for medical record image
Chunjun Hua, Yue Wu, Yiqiao Shi, Menghan Hu, Rong Xie, Guangtao Zhai +1 more
2023· article· en· Computers in Biology and Medicine· Computer Science
distilled prediction:candidate · noneconsensus · none
16
citations
affno abstractunlabeled
LaWa: Using Latent Space for In-Generation Image Watermarking
Ahmad Rezaei, Mohammad Akbari, Saeed Ranjbar Alvar, Arezou Fatemi, Yong Zhang
2024· book-chapter· en· Lecture notes in computer science· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
16
citations
affunlabeled
Robust Black-box Watermarking for Deep Neural Network using Inverse Document Frequency
Mohammad Mehdi Yadollahi, Farzaneh Shoeleh, Sajjad Dadkhah, Ali A. Ghorbani
2021· article· en· 2021 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech)· Computer Science
distilled prediction:candidate · metaepi_narrow+sts+scholarly_communication+open_science+research_integrityconsensus · metaepi_narrow+sts+research_integrity
16
citations
affunlabeled
Secure single-sensor digital camera
Konstantinos N. Plataniotis
2006· article· en· Electronics Letters· Computer Science
distilled prediction:candidate · noneconsensus · none
16
citations
affunlabeled
Flaw in SVD-based Watermarking
Luc Lamarche, Yan Liu, Jiying Zhao
2006· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
15
citations
affunlabeled
M-Ary Phase Modulation for Digital Watermarking
Yongqing Xin, M. Pawlak
2008· article· en· International Journal of Applied Mathematics and Computer Science· Computer Science
distilled prediction:candidate · noneconsensus · none
13
citations
affunlabeled
A New Approach To Color Image Secret Sharing
Rastislav Lukàč, Konstantinos N. Plataniotis, Bogdan Smołka, A.N. Venetsanopoulos
2004· article· en· Computer Science
distilled prediction:candidate · noneconsensus · none
13
citations

How this was built: Screen · Findings · About