MATH+ Adventskaleder: Aufgaben und Lösungen 2024
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.231 | 0.174 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".