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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.

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Computer Science and Software Engineering
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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.

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

106 results · 1 filter active ·
Results by year
20122019
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Categories
Machine labels · sparse coverage
Evidence
Language
Type
Citations
An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
106 works in the cohort · of 4,299,418page 1 of 3

Labels cover 0 of 106 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 106 of 106 works in this cohort. Predictions are machine_predicted_unvalidated. The Gemma side is a direct model label for every work (title-only); the Codex side is a distilled, calibrated classifier. Candidate is the union; consensus is the intersection.

affunlabeled
Cardinality estimation using neural networks
Henry Liu, Mingbin Xu, Ziting Yu, Vincent Corvinelli, Calisto Zuzarte
2015· article· en· Computer Science and Software Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
57
citations
affunlabeled
Interpreting financial time series with SHAP values
Karim El Mokhtari, Ben Peachey Higdon, Ayşe Bener
2019· article· en· Computer Science and Software Engineering· Decision Sciences
machine prediction:candidate · noneconsensus · none
55
citations
affunlabeled
Analyzing auto-scaling issues in cloud environments
Hanieh Alipour, Yan Liu, Abdelwahab Hamou‐Lhadj
2014· article· en· Computer Science and Software Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
21
citations
affunlabeled
Foodie fooderson a conversational agent for the smart kitchen
Prashanti Priya Angara, Miguel Jiménez, Harshit Jain, Roshni Jain, Ulrike Stege, Sudhakar Ganti +2 more
2017· article· en· Computer Science and Software Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
17
citations
affunlabeled
A context-aware machine learning-based approach
Nathalia Nascimento, Paulo Alencar, Carlos Lucena, Donald Cowan
2018· article· en· Computer Science and Software Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
16
citations
affunlabeled
The effect of a collaborative game on group work
Maaz Nasir, Kelly Lyons, Rock Leung, Anthea Bailie, Fred Whitmarsh
2015· article· en· Computer Science and Software Engineering· Psychology
machine prediction:candidate · noneconsensus · none
9
citations
affunlabeled
Ischemic stroke detection using EEG signals
Arooj Ahmed Qureshi, Canxiu Zhang, Rong Zheng, Ahmed Elmeligi
2018· article· en· Computer Science and Software Engineering· Neuroscience
machine prediction:candidate · noneconsensus · none
9
citations
affunlabeled
Microservices in the modern software world
Anthony Kwan, Hans‐Arno Jacobsen, Allen Chan, Suzette Samoojh
2016· article· en· Computer Science and Software Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
7
citations
affunlabeled
An empirical study on change recommendation
Manishankar Mondal, Chanchal K. Roy, Kevin A. Schneider
2015· article· en· Computer Science and Software Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
Mining common morphological fragments from process event logs
Asef Pourmaoumi Hasankiyadeh, Mohsen Kahani, Ebrahim Bagheri, Mohsen Asadi
2014· article· en· Computer Science and Software Engineering· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
Multitenancy benefits in application servers
Panagiotis Patros, Dayal Dilli, Kenneth B. Kent, Michael Dawson, Thomas Watson
2015· article· en· Computer Science and Software Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
4
citations
aboutno affunlabeled
IBM 2016 community hackathon
Chı́nh T. Hoàng, John Liu, Zubaid Bokhari, Allen Chan
2016· article· en· Computer Science and Software Engineering· Engineering
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
String deduplication during garbage collection in virtual machines
Konstantin Nasartschuk, Marcel Dombrowski, Kenneth B. Kent, Aleksandar Micić, Dane Henshall, Charlie Gracie
2016· article· en· Computer Science and Software Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
GitHub's big data adaptor: an eclipse plugin
Ali Sajedi Badashian, Vraj Shah, Eleni Stroulia
2015· article· en· Computer Science and Software Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
2
citations
affaboutunlabeled
TGDB: towards a benchmark for graph databases
Zahid Abul-Basher, Mark Chignell, Parke Godfrey, Nikolay Yakovets
2016· article· en· Computer Science and Software Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Engineering cyber physical systems
Hausi Müller, John Mylopoulos, Marin Litoiu
2015· article· en· Computer Science and Software Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations

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