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Record W4320003114 · doi:10.18280/mmep.090609

Analysis of Kinematic Processes in Physics Based on Functional-Graphical Lines in Mathematics

2022· article· en· W4320003114 on OpenAlex
Zhuldyz Nurmaganbetova, Nurgali Ashirbayev, Manat Shomanbayeva, Raina Bekmoldaeva

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMathematical Modelling and Engineering Problems · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced Theoretical and Applied Studies in Material Sciences and Geometry
Canadian institutionsnot available
Fundersnot available
KeywordsIntuitionKinematicsRepresentation (politics)Computer scienceFunction (biology)Point (geometry)Process (computing)Theoretical computer scienceAlgebra over a fieldMathematicsEpistemologyGeometryPure mathematicsProgramming languagePhysics

Abstract

fetched live from OpenAlex

An analysis of algebra textbooks of 9 grades allowed to state that in the textbooks little attention is paid to the relationship of the quadratic function with real processes, in some textbooks this connection is completely absent. The purpose of the article is to study the kinematic processes in physics based on functional-graphical lines in mathematics. In order to implement such a connection, we have considered problems with physical content and given methods for solving these problems using a functional graphic line (FGL). The analysis of the given graphs opens up wide methodological possibilities of training, since the graphical representation of the physical process makes it more visual and thereby facilitates understanding of the phenomenon under consideration, promotes the development of abstract thinking, intuition, the ability to analyze and compare, and find a more rational way to solve problems. The systematic implementation of such works allows a deeper study of the topic and rational use of the new technique for studying FGL, finding natural connections between disciplines, studying phenomena and processes in technology and nature from the point of view of functional graphic lines.

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.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.764
Threshold uncertainty score0.489

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.015
GPT teacher head0.204
Teacher spread0.189 · 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