Analysis of Kinematic Processes in Physics Based on Functional-Graphical Lines in Mathematics
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".