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A low-cost spectrometer for NMR measurements in the Earth's magnetic field

2010· article· en· W2018885707 on OpenAlexafffund
Carl A. Michal

Bibliographic record

VenueMeasurement Science and Technology · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNMR spectroscopy and applications
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSpectrometerProgrammerMicrocontrollerComputer sciencePhase (matter)Pulse (music)Field (mathematics)MagnetSample (material)Computer hardwareNuclear magnetic resonancePhysicsOpticsElectrical engineeringTelecommunicationsEmbedded systemEngineering

Abstract

fetched live from OpenAlex

We describe and demonstrate an inexpensive, easy-to-build, portable spectrometer for nuclear magnetic resonance measurements in the Earth's magnetic field. The spectrometer is based upon a widely available inexpensive microcontroller, which acts as a pulse programmer, audio-frequency synthesizer and digitizer, replacing what are typically the most expensive specialized components of the system. The microcontroller provides the capability to execute arbitrarily long and complicated sequences of phase-coherent, phase-modulated excitation pulses and acquire data sets of unlimited duration. Suitably packaged, the spectrometer is amenable to measurements in the research lab, in the field or in the teaching lab. The choice of components was heavily weighted by cost and availability, but required no significant sacrifice in performance. Using an existing personal computer, the resulting design can be assembled for as little as US$200. The spectrometer performance is demonstrated with spin-echo and Carr–Purcell–Meiboom–Gill pulse sequences on a water sample.

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: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.018

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 communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.003

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 head0.023
GPT teacher head0.307
Teacher spread0.284 · 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

Citations47
Published2010
Admission routes2
Has abstractyes

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