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Record W2907322778 · doi:10.1002/cmr.b.21401

A low‐cost multi‐channel software‐defined radio‐based NMR spectrometer and ultra‐affordable digital pulse programmer

2018· article· en· W2907322778 on OpenAlexafffund
Carl A. Michal

Bibliographic record

VenueConcepts in Magnetic Resonance Part B · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNMR spectroscopy and applications
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFirmwareProgrammerSoftwareSoftware-defined radioMicrocontrollerInstrumentation (computer programming)Computer scienceSpectrometerSynchronization (alternating current)Open source hardwareComputer hardwareSynchronizingLaptopController (irrigation)Embedded systemChannel (broadcasting)Open sourceTelecommunicationsOperating systemPhysicsOptics

Abstract

fetched live from OpenAlex

Abstract In recent years, a new generation of software‐defined radio (SDR) products has emerged that are well suited for adaptation for NMR instrumentation. The software and hardware of a new NMR spectrometer console based upon an inexpensive SDR product are described. This device is provided with open‐source firmware and drivers which have allowed the customization of its behavior and optimization for use in NMR. In particular, these low‐level modifications have allowed for straightforward synchronization of multiple SDR boards with each other and with other devices. Control of other devices is facilitated by a new digital pulse programmer constructed using an inexpensive open‐source, widely available microcontroller platform. The strategy used for precise, reproducible synchronization of the different components is described in detail. Representative spectra are presented demonstrating both high‐resolution and wide‐line spectroscopy with spectral widths up to 50 MHz.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.818
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.306
Teacher spread0.291 · 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 teacher head, not a consensus.

Study designOther design
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

Citations30
Published2018
Admission routes2
Has abstractyes

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