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Record W6940164835 · doi:10.64336/001c.122560

Snapshot refractive index measurement of a liquid medium based on spatial division of a diffraction grating

2024· article· en· W6940164835 on OpenAlexaff

Bibliographic record

VenueJournal of High School Science · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsOkanagan University CollegeOkanagan College
Fundersnot available
KeywordsRefractive indexDiffractionDiffraction gratingGratingUltrasonic gratingLaserDiffraction efficiencyPhase-contrast imaging

Abstract

fetched live from OpenAlex

This study describes a low-cost snapshot refractive index measurement method based on a spatial separation of diffraction patterns from a diffraction grating. The proposed new device employs a vertical line-shaped laser light source and a transmissive diffraction grating for the spatial separation of the diffraction pattern. It enables the measurement of the refractive index of an unknown liquid easily, quickly, and accurately. More importantly, it enables the simultaneous measurement of the refractive index of multiple liquids in one-shot. In this study, a length-based refractive index measurement method is described. Experiments using two different liquids were performed to demonstrate the feasibility and accuracy of the device. The experimental results showed that the proposed device provided an affordable solution for educational purposes as well as for practical refractive index measurement applications such as water quality monitoring.

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)0.000
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: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.015
GPT teacher head0.243
Teacher spread0.228 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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