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Record W4396696421 · doi:10.1038/s41564-024-01656-3

MicrobioRaman: an open-access web repository for microbiological Raman spectroscopy data

2024· letter· en· W4396696421 on OpenAlexaff
Kang Soo Lee, Zachary Landry, Awais Athar, Uria Alcolombri, Pratchaya Pramoj Na Ayutthaya, David Berry, Philippe de Bettignies, Ji‐Xin Cheng, Gábor Csúcs, Cui Li, Volker Deckert, Thomas Dieing, Jennifer A. Dionne, Ondrej Doskocil, Glen G D’Souza, Cristina García‐Timermans, Notburga Gierlinger, Keisuke Goda, Roland Hatzenpichler, Richard J. Henshaw, Wei E. Huang, Ievgeniia Iermak, Natalia P. Ivleva, Janina Kneipp, Patrick Kubryk, Kirsten Küsel, Tae Kwon Lee, Sung Sik Lee, Bo Ma, Clara Martínez‐Pérez, Pavel Matousek, Rainer U. Meckenstock, Wei Min, Peter Mojzeš, Oliver Müller, Naresh Kumar, Per Halkjær Nielsen, Ioan Notingher, Márton Palatinszky, Fátima C. Pereira, Giuseppe Pezzotti, Zdeněk Pilát, Filip Plesinger, Jürgen Popp, Alexander J. Probst, Alessandra Riva, Amr A. E. Saleh, Ota Samek, H. M. Sapers, Olga T. Schubert, Astrid KM Stubbusch, Loza F. Tadesse, Gordon T. Taylor, Michael Wagner, Jing Wang, Huabing Yin, Yue Yang, Renato Zenobi, Jacopo Zini, Uğis Sarkans, Roman Stocker

Bibliographic record

VenueNature Microbiology · 2024
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSpectroscopy Techniques in Biomedical and Chemical Research
Canadian institutionsYork University
FundersEuropean Molecular Biology LaboratoryGordon and Betty Moore FoundationSimons Foundation
KeywordsRaman spectroscopyWorld Wide WebSpectroscopyOpen sourceComputer scienceChemistryPhysicsOpticsAstronomy

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.006
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesOpen science
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 score0.994
Threshold uncertainty score0.716

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0010.001
Scholarly communication0.0050.004
Open science0.0060.005
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.2140.165

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 head0.043
GPT teacher head0.430
Teacher spread0.387 · 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.

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

Citations34
Published2024
Admission routes1
Has abstractno

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