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Record W2085751335 · doi:10.1021/ed086p68

Assembly of a Modular Fluorimeter and Associated Software: Using LabVIEW in an Advanced Undergraduate Analytical Chemistry Laboratory

2009· article· en· W2085751335 on OpenAlexaff
W. Russ Algar, Melissa Massey, Ulrich J. Krull

Bibliographic record

VenueJournal of Chemical Education · 2009
Typearticle
Languageen
FieldEngineering
TopicExperimental Learning in Engineering
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFluorometerModular designSoftwareChemistryAnalytical Chemistry (journal)Computer scienceSoftware engineeringEnvironmental chemistryProgramming languagePhysics

Abstract

fetched live from OpenAlex

A laboratory activity for an upper-level undergraduate course in instrumental analysis has been created around LabVIEW. Students learn rudimentary programming and interfacing skills during the construction of a fluorimeter assembled from common modular components. The fluorimeter consists of an inexpensive data acquisition module, LED light source, silicon photodiode detector, photodiode amplifier, colored glass filter, and lenses. Students are asked to assemble a working instrument and program its operation in LabVIEW. The fluorimeter is ideally suited for fluorescein. In addition to a calibration curve, students can investigate the pH dependence of fluorescence from fluorescein and the dynamic quenching of fluorescence by iodide. Students generally work in groups of two or three and the laboratory activity takes 16–20 hours to complete.

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)0.002
metaresearch head score (Gemma)0.004
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: Methods · Consensus signal: Methods
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.005

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 head0.007
GPT teacher head0.270
Teacher spread0.263 · 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

Citations19
Published2009
Admission routes1
Has abstractyes

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