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Record W1971762695 · doi:10.1119/1.3596431

Measuring soap bubble thickness with color matching

2011· article· en· W1971762695 on OpenAlexaff
Y. D. Afanasyev, G. Todd Andrews, Christopher G. Deacon

Bibliographic record

VenueAmerican Journal of Physics · 2011
Typearticle
Languageen
FieldEngineering
TopicInnovative Microfluidic and Catalytic Techniques Innovation
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsSoap bubbleSoap filmBubbleMeasure (data warehouse)PhysicsSOAPInterference (communication)OpticsMatching (statistics)Computer scienceMechanicsMathematicsData miningStatisticsTelecommunications

Abstract

fetched live from OpenAlex

This paper describes a laboratory experiment designed to measure thickness variations across a soap bubble. The experiment uses the phenomenon of thin film interference and the principles of color perception to measure the thickness of the soap film at various points across the surface of the bubble. The students review the classical theory of interference and use a digital camera to make the measurements. The apparatus required for the experiment is inexpensive and easy to construct. This experiment is suitable for a senior undergraduate course and can potentially be used to study hydrodynamic effects in soap films.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.024
GPT teacher head0.213
Teacher spread0.188 · 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 designBench or experimental
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

Citations45
Published2011
Admission routes1
Has abstractyes

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