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Record W4380371034 · doi:10.2196/48631

Introducing JMIR Bioinformatics and Biotechnology: A Platform for Interdisciplinary Collaboration and Cutting-Edge Research

2023· editorial· en· W4380371034 on OpenAlexvenueno aff
Ece D. Gamsiz Uzun

Bibliographic record

VenueJMIR Bioinformatics and Biotechnology · 2023
Typeeditorial
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBioinformatics and Genomic Networks
Canadian institutionsnot available
Fundersnot available
KeywordsInformaticsGenomicsData scienceHealth informaticsBioinformaticsEngineeringBiologyComputer scienceHealth carePolitical scienceGenomeGeneticsGene

Abstract

fetched live from OpenAlex

JMIR Bioinformatics and Biotechnology supports interdisciplinary research and welcomes contributions that push the boundaries of bioinformatics, genomics, artificial intelligence, and pathology informatics.

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)0.030
metaresearch head score (Gemma)0.091
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.030
Threshold uncertainty score0.157

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.091
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0060.003
Science and technology studies0.0050.004
Scholarly communication0.0210.008
Open science0.0050.004
Research integrity0.0170.029
Insufficient payload (model declined to judge)0.0270.027

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 head0.015
GPT teacher head0.324
Teacher spread0.309 · 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
GenreEditorial

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

Citations1
Published2023
Admission routes1
Has abstractyes

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