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Record W6968287511 · doi:10.5281/zenodo.15100608

MATH+ Adventskaleder: Aufgaben und Lösungen 2024

2025· book· de· W6968287511 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typebook
Languagede
FieldComputer Science
TopicPolynomial and algebraic computation
Canadian institutionsnot available
FundersDeutsche Forschungsgemeinschaft
KeywordsQuarter (Canadian coin)Work (physics)Term (time)

Abstract

fetched live from OpenAlex

Das Forschungszentrum der Berliner Mathematik MATH+ wird als Exzellenzcluster im Rahmen der Exzellenzstrategie des Bundes und der Länder gefördert. MATH+ betreibt anwendungsgetriebene mathematische Forschung mit gesellschaftlicher Relevanz. Der Mathe-Adventskalender wurde 2004 ersten Mal vom MATH+ Vorgänger Matheon angeboten. Seitdem gibt es den Mathe-Adventskalender jährlich. Forschende, Promovierende und Studierende von MATH+ sowie von 4TU.AMI haben 24 Mathematikaufgaben entwickelt, die an ihre Forschung angelehnt sind, um aktuelle Forschung Schülerinnen und Schülern näher zubringen. Diese kniffligen Mathematikaufgaben sind in diesem Buch zu finden. Die Aufgaben stammen aus den Bereichen der Kombinatorik, Graphentheorie, Algebra, Analysis, Geometrie, Stochastik, Topologie und vielen weiteren. Zu jeder Aufgabe gibt es eine Lösung.

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.

How this classification was reachedexpand

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.462
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0040.000
Scholarly communication0.0040.001
Open science0.0050.007
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.046

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 head0.025
GPT teacher head0.250
Teacher spread0.225 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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Same venueZenodo (CERN European Organization for Nuclear Research)Same topicPolynomial and algebraic computationFrench-language works237,207