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Record W2792521007 · doi:10.7566/jpscp.21.011049

BnmrOffice: A Free Software for β-<scp>nmr</scp> Data Analysis

2018· article· en· W2792521007 on OpenAlexaff
H. Saadaoui

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicMagnetism in coordination complexes
Canadian institutionsTRIUMF
Fundersnot available
KeywordsComputer scienceSoftwareProgramming language

Abstract

fetched live from OpenAlex

A data-analysis framework with a graphical user interface (GUI) is developed to analyze -nmr spectra in an automated and intuitive way. This program, named BnmrOffice is written in C++ and employs the QT libraries and tools for designing the GUI, and the CERN's Minuit optimization routines for minimization. The program runs under multiple platforms, and is available for free under the terms of the GNU GPL standards. The GUI is structured in tabs to search, plot and analyze data, along other functionalities. The user can tweak the minimization options; and fit multiple data files (or runs) using single or global fitting routines with pre-defined or new models. Currently, BnmrOffice reads TRIUMF's MUD data and ASCII files, and can be extended to other formats.

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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.212
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.056
GPT teacher head0.319
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 teacher head, not a consensus.

Study designNot applicable
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

Citations2
Published2018
Admission routes1
Has abstractyes

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