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Record W4405977110 · doi:10.29173/scientia10

Reading Galvanometers

2024· article· en· W4405977110 on OpenAlexvenueaboutno aff
Erich Weidenhammer, V. J. Fisher, Chen‐Pang Yeang, Patrick Finnigan

Bibliographic record

VenueScientia Canadensis Canadian Journal of the History of Science Technology and Medicine · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicHistory of Science and Natural History
Canadian institutionsnot available
Fundersnot available
KeywordsGalvanometerContext (archaeology)Reading (process)ElectricityMathematics educationSelection (genetic algorithm)LandmarkComputer scienceEngineeringEngineering ethicsPolitical scienceElectrical engineeringPsychologyHistoryPhysicsArtificial intelligenceOpticsLaw

Abstract

fetched live from OpenAlex

The methodology of experimental reenactment has typically been used by historians to better understand landmark experiments. In this paper, we apply this approach to the galvanometer, an instrument so fundamental to the study of electricity that we may consider it infrastructure underlying the teaching of physics and engineering through the 19th century and well into the 20th centuries. We study a selection of galvanometers from the University of Toronto Scientific Instruments Collection, using them to explore their institutional context. Finally, we operate a representative galvanometer to explore several of the teaching experiments undertaken by engineering and physics students of the late 19th and early 20th centuries.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.429
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.001
Science and technology studies0.0010.045
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.212
Teacher spread0.193 · 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.

Study designNot applicable
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
Published2024
Admission routes2
Has abstractyes

Explore more

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