Check Claims Before You Publish

I could not locate any publication records, OpenAlex author match, or other bibliographic metadata for the name "San Momben-Abolfath" in the OpenAlex query results you provided. To produce a rigorous, evidence-based author critique (citation metrics, coauthor network, topical footprint, citation timeline, reproducibility signals), I need primary bibliographic identifiers (ORCID, Scopus ID, Web of Science ID), a list of publications, or PDF full texts.

What I can do next: run targeted searches across OpenAlex/CrossRef/Unpaywall, extract raw citation counts and altmetrics, compute h-index, build coauthor and topic graphs, and generate publication-level evidence summaries — provided the author’s publication list or identifiers are uploaded or shared.

• Author publication list (DOIs preferred) or PDF copies of papers
• Author identifiers (ORCID, Scopus Author ID, ResearcherID, Google Scholar link)
• Any public datasets, preprints, or GitHub repositories linked to the author

All quantitative author-level metrics (total publications, total citations, h-index, citation velocity, field-weighted metrics, coauthor network centrality, reproducibility indicators) require linking to primary bibliographic records or full-text data. Without matches in bibliographic indexes, any metric would be speculative and unscientific.

1. Publication timeline (year-by-year counts + citations per paper)
2. h-index, i10-index, total citations (computed from CrossRef/OpenAlex/Scopus where available)
3. Coauthor network graph (nodes = authors, edges = coauthorship weight)
4. Topic fingerprint via title/abstract LDA or keyword frequency
5. Paper-level reproducibility flags (data/code availability, preregistration, corrigenda)

1. Ingest DOIs / PDF full-texts and extract structured metadata (title, authors, affiliations, journal, year, DOI).
2. Query OpenAlex/CrossRef/Unpaywall/Dimensions to gather citation counts, references, altmetrics, and data/code availability flags.
3. Compute bibliometric indicators (h-index, m-index, citation acceleration, field-normalized citation impact).
4. Build coauthor and citation networks; compute centrality (degree, betweenness) and visualize with interactive graphs.
5. Generate per-paper evidence cards summarizing methods, sample sizes, primary data availability, and any corrections/retractions.