MétaCan
Menu
Back to cohort
Record W3215321321 · doi:10.31349/revmexfise.19.010204

Didactical situations to treat Lorentz and Galileo transformations in theoretical physics

2021· article· en· W3215321321 on OpenAlexaff
Sérgio Antônio de Souza Farias, Damião Pedro Meira Filho, Jorge Kysnney Santos Kamassury

Bibliographic record

VenueRevista Mexicana de Física E · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Digital Technologies
Canadian institutionsWestern University
Fundersnot available
KeywordsGalileo (satellite navigation)Context (archaeology)Set (abstract data type)ElectromagnetismRelevance (law)Lorentz transformationTheoretical physicsMathematical practiceEpistemologyPhysicsCalculus (dental)Mathematics educationMathematicsComputer scienceClassical mechanicsQuantum mechanicsPhilosophy

Abstract

fetched live from OpenAlex

Notions of Electromagnetism and Special Theory of Relativity (STR) require important mathematical knowledge applied to theoretical physics. Recognizing pedagogical difficulties in the teaching of theoretical physics, the Theory of Didactical Situations (TDS), which consists of a set of practices that aim to contribute to the improvement of mathematics teaching. In this context, the present work is motivated to present a set of practices based on TDS with a focus on teaching Electromagnetism and STR, where problems that require an understanding of the transformations of Galileo and Lorentz. Specifically, the didactic situation is constructed by means of four problem proposals, while in the adidatic situation, the student is invited to understand the roles of these transformations in the study of these problems. Ultimately, the relevance of the educator in the institutionalization situation is reinforced, a moment when it must be clarified how all mathematical relations are strongly related to physical principles.

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)0.006
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.006
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.012
Scholarly communication0.0040.004
Open science0.0020.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.025
GPT teacher head0.352
Teacher spread0.327 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations4
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueRevista Mexicana de Física ESame topicEducation and Digital TechnologiesFrench-language works237,207