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Record W4415340732 · doi:10.1016/j.tcs.2025.115597

Degrees are useless in Snort when measuring temperature

2025· article· en· W4415340732 on OpenAlex
Svenja Huntemann, Tomasz Maciosowski

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueTheoretical Computer Science · 2025
Typearticle
Languageen
FieldComputer Science
TopicEvolutionary Algorithms and Applications
Canadian institutionsMemorial University of NewfoundlandMount Saint Vincent University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsVertex (graph theory)Degree (music)GraphMeasure (data warehouse)Simple (philosophy)Position (finance)

Abstract

fetched live from OpenAlex

Snort is a two-player game played on a simple graph in which players alternately colour a vertex such that they do not colour adjacent to their opponent’s vertex. In combinatorial game theory, the temperature of a position is a measure of the urgency of moving first. It is known that the temperature of Snort in general is infinite ( K 1 , n has temperature n ). We show that for all constants c there is a game of Snort for which the difference between the temperature and the maximum degree of the board is at least c . We do so by constructing a family of positions in which the temperature grows twice as fast as the maximum degree of the board.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.773
Threshold uncertainty score0.505

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.241
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it