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Record W4408611484 · doi:10.1371/journal.pbio.3003070

The IBEX Knowledge-Base: A central resource for multiplexed imaging techniques

2025· article· en· W4408611484 on OpenAlexafffund
Andrea J. Radtke, Ifeanyichukwu U. Anidi, Leanne Arakkal, Armando Arroyo-Mejías, Rebecca T. Beuschel, Katy Börner, Colin J. Chu, Beatrice Clark, Menna R. Clatworthy, Jake Colautti, Fabian Coscia, Joshua Croteau, Saven Denha, Rose Dever, Walderez O. Dutra, Sonja Fritzsche, Spencer Fullam, Michael Y. Gerner, Anita Gola, Kenneth J. Gollob, Jonathan M. Hernandez, Jyh Liang Hor, Hiroshi Ichise, Zhixin Jing, Danny Jonigk, Evelyn Kandov, Wolfgang Kastenmüller, Joshua F. E. Koenig, Rosa K Kortekaas, Aanandita Kothurkar, Alexandra Y. Kreins, Ian T. Lamborn, Yuri Lin, Kátia L.P. Morais, Aleksandra Lunich, Jean CS Luz, Ryan B. MacDonald, Chen Makranz, Vivien I. Maltez, John E. McDonough, Ryan V. Moriarty, Juan Moisés Ocampo‐Godínez, Vitoria M Olyntho, Annette Oxenius, Kartika Padhan, Kirsten Remmert, Nathan Richoz, Edward C. Schrom, Wanjing Shang, Lihong Shi, Rochelle M. Shih, Emily Speranza, Salome Stierli, Sarah A. Teichmann, Tibor Z. Veres, Megan Vierhout, Brianna T. Wachter, Adam K. Wade‐Vallance, Margaret Williams, Nathan Zangger, Ronald N. Germain, Ziv Yaniv

Bibliographic record

VenuePLoS Biology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSingle-cell and spatial transcriptomics
Canadian institutionsSt. Joseph’s Healthcare HamiltonMcMaster University
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institute of Allergy and Infectious DiseasesNational Cancer InstituteNIHR Cambridge Biomedical Research CentreWellcome TrustBiotechnology and Biological Sciences Research CouncilNational Institutes of HealthInstituto Nacional de Ciência e Tecnologia de Doenças TropicaisCommon FundConselho Nacional de Desenvolvimento Científico e TecnológicoInstituto Politécnico NacionalNational Institute of General Medical SciencesInstitute of Circulatory and Respiratory HealthDivision of Intramural Research, National Institute of Allergy and Infectious DiseasesNHS Blood and TransplantNational Institute for Health and Care ResearchBundesministerium für Bildung und ForschungInstitute of Infection and ImmunityFundação de Amparo à Pesquisa do Estado de São PauloConsejo Nacional de Ciencia y TecnologíaJ.P. Bickell FoundationFundação de Amparo à Pesquisa do Estado de Minas GeraisCanadian Allergy, Asthma and Immunology FoundationCanadian Institutes of Health ResearchDamon Runyon Cancer Research Foundation
KeywordsBiologyResource (disambiguation)Knowledge baseComputational biologyMultiplexingResource useData scienceComputer scienceArtificial intelligenceEnvironmental resource management

Abstract

fetched live from OpenAlex

Multiplexed imaging is a powerful approach in spatial biology, although it is complex, expensive and labor-intensive. Here, we present the IBEX Knowledge-Base, a central resource for reagents, protocols and more, to enhance knowledge sharing, optimization and innovation of spatial proteomics techniques.

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)0.009
metaresearch head score (Gemma)0.023
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: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.023
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0120.010
Science and technology studies0.0020.001
Scholarly communication0.0120.008
Open science0.0110.007
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0300.060

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 head0.012
GPT teacher head0.267
Teacher spread0.255 · 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
GenreDataset

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

Citations3
Published2025
Admission routes2
Has abstractyes

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