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Record W4294315264 · doi:10.1063/5.0087903

Elastic interactions in physics are reflections in geometry

2022· article· en· W4294315264 on OpenAlexafffund
François Dubeau

Bibliographic record

VenueAIP Advances · 2022
Typearticle
Languageen
FieldEngineering
TopicMaterial Science and Thermodynamics
Canadian institutionsUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsConic sectionBasis (linear algebra)Intersection (aeronautics)Geometrical opticsClassical mechanicsSimple (philosophy)PhysicsInterpretation (philosophy)Theoretical physicsIdeal (ethics)GeometryPoint (geometry)Reflection (computer programming)Line (geometry)KeplerMathematicsOpticsComputer scienceLawStars

Abstract

fetched live from OpenAlex

A simple standard problem in physics is the study of elastic collisions between elements of an ideal system, which consists of two point masses and a wall. Based on energy and momentum conservation laws, solving the problem consists in finding the intersection of a straight line with a conic. Relationships between the solutions are easily obtained if we consider the right (fundamental) basis to express the solutions. The geometric interpretation follows easily: moving from one point to another on a conic using directions given by this basis. With simple changes in variables, reflections and rotations appear clearly. Similarities with other phenomena such as Heron’s reflection principle in optics and Kepler’s second law of planetary motion are pointed out.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.013
Scholarly communication0.0030.009
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.002

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 head0.013
GPT teacher head0.277
Teacher spread0.264 · 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

Citations1
Published2022
Admission routes2
Has abstractyes

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