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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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Synthesis lectures on games and computational intelligence
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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.

20 results · 1 filter active ·
Results by year
20172025
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Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
20 works in the cohort · of 4,299,418page 1 of 1

Labels cover 0 of 20 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 20 of 20 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.

affno abstractunlabeled
Neural Networks—Introduction
Matthew Guzdial, Sam Snodgrass, Adam Summerville
2025· book-chapter· en· Synthesis lectures on games and computational intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
7
citations
affno abstractunlabeled
On the Design of Game-Playing Agents
Eun-Youn Kim, Daniel Ashlock
2017· article· en· Synthesis lectures on games and computational intelligence· Social Sciences
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
Generative AI
Matthew Guzdial, Sam Snodgrass, Adam Summerville
2025· book-chapter· en· Synthesis lectures on games and computational intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Grid-Based DNN PCGML
Matthew Guzdial, Sam Snodgrass, Adam Summerville
2022· book-chapter· en· Synthesis lectures on games and computational intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
An Introduction to ML Through PCG
Matthew Guzdial, Sam Snodgrass, Adam Summerville
2025· book-chapter· en· Synthesis lectures on games and computational intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Mixed-Initiative PCGML
Matthew Guzdial, Sam Snodgrass, Adam Summerville
2025· book-chapter· en· Synthesis lectures on games and computational intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Sequence-Based DNN PCGML
Matthew Guzdial, Sam Snodgrass, Adam Summerville
2025· book-chapter· en· Synthesis lectures on games and computational intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Introduction
Matthew Guzdial, Sam Snodgrass, Adam Summerville
2025· book-chapter· en· Synthesis lectures on games and computational intelligence· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
Constraint-Based PCGML Approaches
Matthew Guzdial, Sam Snodgrass, Adam Summerville
2025· book-chapter· en· Synthesis lectures on games and computational intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
PCGML Process Overview
Matthew Guzdial, Sam Snodgrass, Adam Summerville
2025· book-chapter· en· Synthesis lectures on games and computational intelligence· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Reinforcement Learning PCG
Matthew Guzdial, Sam Snodgrass, Adam Summerville
2025· book-chapter· en· Synthesis lectures on games and computational intelligence· Engineering
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Classical PCG
Matthew Guzdial, Sam Snodgrass, Adam Summerville
2025· book-chapter· en· Synthesis lectures on games and computational intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Terrain Maps
Daniel Ashlock
2018· book-chapter· en· Synthesis lectures on games and computational intelligence· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Open Problems
Matthew Guzdial, Sam Snodgrass, Adam Summerville
2025· book-chapter· en· Synthesis lectures on games and computational intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Grid-Based DNN PCGML
Matthew Guzdial, Sam Snodgrass, Adam Summerville
2025· book-chapter· en· Synthesis lectures on games and computational intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Probabilistic PCGML Approaches
Matthew Guzdial, Sam Snodgrass, Adam Summerville
2025· book-chapter· en· Synthesis lectures on games and computational intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Probabilistic PCGML Approaches
Matthew Guzdial, Sam Snodgrass, Adam Summerville
2022· book-chapter· en· Synthesis lectures on games and computational intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Resources and Conclusions
Matthew Guzdial, Sam Snodgrass, Adam Summerville
2025· book-chapter· en· Synthesis lectures on games and computational intelligence· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
An Introduction of ML Through PCG
Matthew Guzdial, Sam Snodgrass, Adam Summerville
2022· book-chapter· en· Synthesis lectures on games and computational intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Contrasting Representations for Maze Generation
Daniel Ashlock
2018· book-chapter· en· Synthesis lectures on games and computational intelligence· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations

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