Bibliographic record
Abstract
Along with explaining the Saito-Kurokawa lift, Eichler and Zagier's book gives the main structural theorems for Jacobi forms on the full modular subgroup. Since then much work has been published in papers generalizing these results to different types of Jacobi forms, but very little work has been done generalizing the theory to Jacobi forms for congruence subgroups. A large part of this thesis will be aimed at generalizing the work of Eichler-Zagier's book to Jacobi forms for congruence subgroups. In particular, we describe the structure for the Jacobi-Eisenstein space of the congruence subgroup Gamma(N). We will also find a bound on the number of Fourier coefficients needed to determine a Jacobi form for a congruence subgroup. The latter part of this work will cover the theory of theta series and the corresponding theory of Jacobi-theta series. The motivating problem for this thesis is to find a basis for the space of Jacobi forms for congruence subgroups.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 0.005 |
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".