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Record W6930289251 · doi:10.5281/zenodo.1303432

sympy/sympy: SymPy 1.2rc1

2018· other· en· W6930289251 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2018
Typeother
Languageen
FieldMathematics
TopicStatistical Distribution Estimation and Applications
Canadian institutionsNexen (Canada)
Fundersnot available
KeywordsCode (set theory)Source codeSoftwareMD5

Abstract

fetched live from OpenAlex

See https://github.com/sympy/sympy/wiki/release-notes-for-1.2 for the release notes. Filename Description size md5 sympy-1.2rc1.tar.gz The SymPy source installer. 5.2M 4f3840ab6134954b7f309aa2b0f7edbf sympy-docs-html-1.2rc1.zip Html documentation. This is the same as the online documentation. 7.1M 28abd7a1a62bead851804534d32176ea sympy-docs-pdf-1.2rc1.pdf Pdf version of the html documentation. 6.2M 7dbf4efcb4d077c5bdff87372b9d7b22 Note: Do not download the Source code (zip) or the Source code (tar.gz) files below.

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)0.001
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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: Software · Consensus signal: none
Teacher disagreement score0.221
Threshold uncertainty score0.316

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.003
Science and technology studies0.0020.001
Scholarly communication0.0060.010
Open science0.0040.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.7790.860

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 head0.081
GPT teacher head0.328
Teacher spread0.247 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreSoftware

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
Published2018
Admission routes1
Has abstractyes

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Same venueZenodo (CERN European Organization for Nuclear Research)Same topicStatistical Distribution Estimation and ApplicationsFrench-language works237,207