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Record W6949935799 · doi:10.5281/zenodo.4456618

xieguigang/mzkit: BioNovoGene Mzkit

2021· other· en· W6949935799 on OpenAlexaff

Bibliographic record

VenueFigshare · 2021
Typeother
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsOntario Genomics
Fundersnot available
KeywordsRaw dataOpen sourceFile formatData sourceData formatMass spectrometry

Abstract

fetched live from OpenAlex

Mzkit is an open source raw data file toolkit for mass spectrometry data analysis, provides by the BioNovoGene corporation. The features of mzkit inlcudes: raw data file content viewer(XIC/TIC/Mass spectrum plot), MS-imaging, build molecule network, formula de-novo search and de-novo annotation. This open source mass spectrometry data toolkit is developed at the BioDeep R&D laboratory and brought to you by BioNovoGene corporation. Raw Data View in mzkit View LC-MS un-targeted data file: mzML, mzXML View GC-MS targeted data file: CDF View LC-MS/MS targeted MRM data: mzML MS-Imaging supported

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Software · Consensus signal: Software
Teacher disagreement score0.212
Threshold uncertainty score0.710

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0050.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.2120.225

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 head0.064
GPT teacher head0.330
Teacher spread0.266 · 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 designNot applicable
Domainnot available
GenreSoftware

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
Published2021
Admission routes1
Has abstractyes

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