On the public citation graph

https://doi.org/10.2139/ssrn.4680232

0 signed · 20 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/path.966openalex-extracted
Liver metastases from colorectal adenocarcinomas grow in three patterns with different angiogenesis and desmoplasia
inferredcites →https://doi.org/10.1007/978-1-4939-2550-6_14openalex-extracted
Isolation of Extracellular Vesicles for Proteomic Profiling
inferredcites →https://doi.org/10.1007/978-3-319-01721-1openalex-extracted
Modal Interval Analysis: New Tools for Numerical Information
inferredcites →https://doi.org/10.1007/bf00119986openalex-extracted
What can interval analysis do for global optimization?
inferredcites →https://doi.org/10.1007/bf03186528openalex-extracted
Theory of an interval algebra and its application to numerical analysis
inferredcites →https://doi.org/10.1007/s13347-019-00382-7openalex-extracted
Solving the Black Box Problem: A Normative Framework for Explainable Artificial Intelligence
inferredcites →https://doi.org/10.1016/j.ccell.2016.10.009openalex-extracted
Extracellular Vesicles in Cancer: Cell-to-Cell Mediators of Metastasis
inferredcites →https://doi.org/10.1017/s0962492904000194openalex-extracted
Complete search in continuous global optimization and constraint satisfaction
inferredcites →https://doi.org/10.1038/bjc.2017.334openalex-extracted
International consensus guidelines for scoring the histopathological growth patterns of liver metastasis
inferredcites →https://doi.org/10.1038/nm.4197openalex-extracted
Vessel co-option mediates resistance to anti-angiogenic therapy in liver metastases
inferredcites →https://doi.org/10.1038/s41598-021-82952-4openalex-extracted
Dogs display owner-specific expectations based on olfaction
inferredcites →https://doi.org/10.1038/s42256-021-00338-7openalex-extracted
AI for radiographic COVID-19 detection selects shortcuts over signal
inferredcites →https://doi.org/10.1080/20013078.2018.1535750openalex-extracted
Minimal information for studies of extracellular vesicles 2018 (MISEV2018): a position statement of the International Society for Extracellular Vesicles and update of the MISEV2014 guidelines
inferredcites →https://doi.org/10.1137/1.9780898717716openalex-extracted
Introduction to Interval Analysis
inferredcites →https://doi.org/10.1201/9780203026922openalex-extracted
Global Optimization Using Interval Analysis
inferredcites →https://doi.org/10.1515/cclm.2011.672openalex-extracted
Canine olfactory detection of cancer versus laboratory testing: myth or opportunity?
inferredcites →https://doi.org/10.1634/theoncologist.9-suppl_1-11openalex-extracted
Targeted Therapy of Colorectal Cancer: Clinical Experience with Bevacizumab
inferredcites →https://doi.org/10.3402/jev.v4.30087openalex-extracted
Applying extracellular vesicles based therapeutics in clinical trials – an ISEV position paper
inferredcites →https://doi.org/10.48550/arxiv.1609.04747openalex-extracted
An overview of gradient descent optimization algorithms
inferredcites →https://doi.org/10.48550/arxiv.1802.09941openalex-extracted
Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.