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Record W3002305908 · doi:10.6000/1929-7092.2019.08.71

Developing Formulas for Quick Calculation of Polyhedron Volume in Spatial Geometry: Application to Vietnam

2019· article· en· W3002305908 on OpenAlexvenueno aff
Bùi Anh Tuấn, Michael McAleer, Nguyen Thi Tieu Dang, Kim-Hung Pho

Bibliographic record

VenueJournal of Reviews on Global Economics · 2019
Typearticle
Languageen
FieldMathematics
TopicMathematics Education and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsPolyhedronVolume (thermodynamics)ComputationComputer scienceSoftwareGeometryWork (physics)Perspective (graphical)MathematicsMathematical optimizationAlgorithmMechanical engineeringEngineering

Abstract

fetched live from OpenAlex

In the age of globalization, an effective leadership skill is the ability for quick calculation of work-related problems. From an economic perspective, fast computation often provides a competitive advantage in business, where speed, efficiency and accuracy are required. Quick calculation techniques are a central problem in modern mathematics because it shortens the time for solving technical problems. The purpose of the paper is to provide an explanation that will lead to a quick solution to a volume problem. Specifically, some convenient formulas are provided for quick calculation of the volume of the common polyhedron, together with a number of multiple-choice questions with IATA software to practice. Based on the evaluation results, reliable multiple-choice questions are used for an empirical study in Can Tho City, Vietnam on the effectiveness of the formulas for quick calculation of the polyhedron volume in spatial geometry. Statistical analysis shows that quick formulas help students to complete lessons at a higher rate, thereby contributing to improvements in the effectiveness of teaching geometry, especially the volume of the Polyhedron.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.689
Threshold uncertainty score0.476

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.064
GPT teacher head0.387
Teacher spread0.323 · 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 teacher head, 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
Published2019
Admission routes1
Has abstractyes

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