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
International Conference on Artificial Intelligence and Statistics
Topic
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.

69 results · 1 filter active ·
Results by year
20052021
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.
69 works in the cohort · of 4,299,418page 2 of 2

Labels cover 0 of 69 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 69 of 69 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affno abstractunlabeled
Quantum Tensor Networks, Stochastic Processes, and Weighted Automata
Sandesh Adhikary, Siddarth Srinivasan, Jacob Miller, Guillaume Rabusseau, Byron Boots
2021· article· en· International Conference on Artificial Intelligence and Statistics· Computer Science
distilled prediction:candidate · noneconsensus · none
4
citations
affunlabeled
Improved Semi-Supervised Learning with Multiple Graphs
Krishnamurthy Viswanathan, Sushant Sachdeva, Andrew Tomkins, Sujith Ravi
2019· article· en· International Conference on Artificial Intelligence and Statistics· Computer Science
distilled prediction:candidate · noneconsensus · none
3
citations
affno abstractunlabeled
Sequential Graph Matching with Sequential Monte Carlo.
Seong-Hwan Jun, Samuel W. K. Wong, James V. Zidek, Alexandre Bouchard‐Côté
2017· article· en· International Conference on Artificial Intelligence and Statistics· Computer Science
distilled prediction:candidate · scholarly_communicationconsensus · none
2
citations
affno abstractunlabeled
Detection and Defense of Topological Adversarial Attacks on Graphs
Yingxue Zhang, Florence Regol, Soumyasundar Pal, Sakif Khan, Liheng Ma, Mark Coates
2021· article· en· International Conference on Artificial Intelligence and Statistics· Computer Science
distilled prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Adaptive Approximate Policy Iteration
Botao Hao, Nevena Lazic, Yasin Abbasi-Yadkori, Pooria Joulani, Csaba Szepesvári
2021· article· en· International Conference on Artificial Intelligence and Statistics· Computer Science
distilled prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Parallel Markov Chain Monte Carlo via Spectral Clustering
Guillaume Basse, Aaron Smith, Natesh S. Pillai
2016· article· en· International Conference on Artificial Intelligence and Statistics· Mathematics
distilled prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Domain Adaptation: A Small Sample Statistical Approach
Ruslan Salakhutdinov, Sham M. Kakade, Dean P. Foster
2012· article· en· International Conference on Artificial Intelligence and Statistics· Computer Science
distilled prediction:candidate · noneconsensus · none
0
citations
affunlabeled
On the Reducibility of Submodular Functions
Jincheng Mei, Hao Zhang, Bao‐Liang Lu
2016· article· en· International Conference on Artificial Intelligence and Statistics· Computer Science
distilled prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About