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Record W7096675959

Supplementary Tables for “Numerical Results on Class Groups of Imaginary Quadratic Fields”

2008· article· en· W7096675959 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMathematics
TopicAlgebraic Geometry and Number Theory
Canadian institutionsnot available
Fundersnot available
KeywordsTable (database)Class (philosophy)Prime (order theory)Quadratic equationNorm (philosophy)Prime numberContingency table
DOInot available

Abstract

fetched live from OpenAlex

We present supplemental tables and additional data that extend that presented in [7]. Data corresponding to all the conjectures mentioned in [7] are included, and all tables are complete, including previously published results. In addition, two corrections to the data in [7] are included: – Originally, we only listed first occurrences of p-Sylow subgroups for primes p ≤ 173. In this paper, we present the entire list, for primes p ≤ 389. See Table 7. – When listing the first ∆ needing prime ideals of norm up to p, we pointed out an anomaly in the data at p = 181. Subsequent analysis has shown this to be a bug in our statistics gathering program. The data no longer contains any anomalies of this sort. See Table 15. Bounds on L(1, χ) There has been significant interest [2, 3, 6, 11] in the extreme values of L(1, χ∆) due to the relationship between it and the class number h∆. This can be seen in the analytic class number formula, L(1, χ∆) = h∆π where extreme values of L(1, χ∆) correspond to extreme values of h∆. In [10], Littlewood developed bounds on L(1, χ∆), namely that under the ERH, {1 + o(1)}(c1 log log ∆) −1 < L(1, χ∆) < {1 + o(1)}c2 log log(∆) , (0.1) where c1 and c2 are defined as follows: c1 = 12e γ /π 2 and c2 = 2e γ when 2 ∤ ∆ c1 = 8e γ /π 2 and c2 = e γ when 2 | ∆. ⋆ All three authors are supported in part by NSERC of Canada. In [11], Shanks investigated Littlewood’s bounds, and defined two values he termed the upper and lower Littlewood indices ULI = L(1, χ∆)/(c2 log log ∆) LLI = L(1, χ∆)c1 log log ∆. These indices effectively ignore the o(1) given in Littlewood’s bounds. We would expect extreme values of the LLI and the ULI to approach 1. Finally, as in [11], we define the function

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.615
Threshold uncertainty score0.549

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.007
Science and technology studies0.0010.000
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.6150.201

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 head0.039
GPT teacher head0.300
Teacher spread0.261 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2008
Admission routes1
Has abstractyes

Explore more

Same topicAlgebraic Geometry and Number TheoryFrench-language works237,207