MétaCan
Menu
Back to cohort
Record W4224237201 · doi:10.1117/12.2628084

Complex number and point-set topology

2022· article· en· W4224237201 on OpenAlexaff
Junchi Yang, Yunyang Ye, Chengyue zhang, Hongrun Li

Bibliographic record

VenueInternational Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021) · 2022
Typearticle
Languageen
FieldComputer Science
TopicConstraint Satisfaction and Optimization
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsTopology (electrical circuits)Set (abstract data type)Point (geometry)Euler characteristicComputer scienceEuler's formulaPath (computing)MathematicsContradictionSet theoryTheoretical computer scienceDiscrete mathematicsPure mathematicsCombinatoricsGeometry

Abstract

fetched live from OpenAlex

Complex numbers, is an important part of modern mathematics. By using the complex number, we can solve many geometry problems. However, it can also be applied to physics. For example, it can play an important role in calculating alternating current. In this paper, we will introduce the definition and several properties of the complex number, also including the point-set topology. We try to prove the important theorems about the complex number; for instance, de Moivre's formula, the problems of connected set and path-connected set; also, the main idea that we cannot compare two complex numbers. To achieve these goals, we will use induction, Euler’s formula; the basic concept of topology, and proving by contradiction.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.005
Scholarly communication0.0040.008
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.043
GPT teacher head0.310
Teacher spread0.267 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueInternational Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021)Same topicConstraint Satisfaction and OptimizationFrench-language works237,207