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Record W2047184448 · doi:10.1021/ed400366e

A Cost-Effective Optical Device for the Characterization of Liquid Crystals

2014· article· en· W2047184448 on OpenAlexafffund
Brian Millier, Gianna Aleman Milán

Bibliographic record

VenueJournal of Chemical Education · 2014
Typearticle
Languageen
FieldMaterials Science
TopicLiquid Crystal Research Advancements
Canadian institutionsDalhousie University
FundersDalhousie University
KeywordsCharacterization (materials science)NanotechnologyMaterials scienceLiquid crystalEngineering physicsProcess engineeringOpticsOptoelectronicsEngineeringPhysics

Abstract

fetched live from OpenAlex

The design and construction of an apparatus to measure the optical birefringence of a liquid crystal is described. The instrument also includes temperature control and monitoring circuitry to allow for the measurement of the nematic-to-isotropic phase transition temperature. An important feature of this design is that the students are able to build the optical bench section of the instrument from a kit of parts supplied. The electronics instrumentation for the illuminator, photometer, and temperature controller functions are all low-cost designs using common components, yet provide more than adequate accuracy for the measurements required. The entire instrument cost is $430, an estimated cost reduction of approximately $3000 compared to the design previously proposed by Waclawik et al. This instrumentation is suitable for second or third-year undergraduate students in materials science or physical chemistry courses.

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)0.001
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: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.003

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 head0.027
GPT teacher head0.359
Teacher spread0.332 · 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
GenreMethods

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
Published2014
Admission routes2
Has abstractyes

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