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Record W2990516456 · doi:10.1088/1361-6552/ab525d

Determining Planck’s constant with LEDs—what could possibly go wrong?

2019· article· en· W2990516456 on OpenAlexaff
Dean Zollman, I. G. Bearden

Bibliographic record

VenuePhysics Education · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicExperimental and Theoretical Physics Studies
Canadian institutionsInstitute of Particle Physics
Fundersnot available
KeywordsLight-emitting diodePlanckPhysicsPlanck energyPlanck constantConstant (computer programming)Energy (signal processing)DiodeOptoelectronicsOpticsQuantum mechanicsComputer sciencePlanck scale

Abstract

fetched live from OpenAlex

Abstract Light emitting diodes have been used to determine Planck’s constant in introductory physics laboratories. One common method relies on the energy of the light emitted by the LED and its relation to the energy gap in the solid of which the diode is composed. However, there could be a problem with the data that are collected for this experiment. For some LEDs the energy of the light emitted from the LED can be quite different from the gap energy. If these LEDs are used for the experiment, the results will give different results for Planck’s constant.

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)0.015
metaresearch head score (Gemma)0.064
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.064
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.002
Science and technology studies0.0030.008
Scholarly communication0.0060.022
Open science0.0050.004
Research integrity0.0050.013
Insufficient payload (model declined to judge)0.0130.007

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 head0.006
GPT teacher head0.251
Teacher spread0.245 · 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

Citations7
Published2019
Admission routes1
Has abstractyes

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