Overview
Manual synthesis cannot keep pace with a fast-growing research literature, and ad-hoc
reviews bind no evidence to a reproducible pipeline. We present a configurable,
reproducible meta-analysis framework that takes a single search term and produces a
complete quantitative portrait of its literature. For this instance the term is
Modafinil. The pipeline dispatches across 7 literature
engines (arXiv, OpenAlex, Semantic Scholar, Crossref, PubMed, SovietRxiv, and ChinaRxiv), each degrading gracefully to a skipped source when an API
key or the network is unavailable, then merges and de-duplicates records by a canonical
identifier hierarchy (DOI $>$ arXiv ID $>$ Semantic Scholar ID $>$ OpenAlex ID $>$ title
digest) into a corpus of $N = 2302$ records spanning 2000--2026
(26 years). Records are classified into a configurable 6-bucket
subfield taxonomy (Clinical Sleep, Cognition, Pharmacology, Psychiatry, Safety, and Neuroscience); the largest subfield is Clinical Sleep
(64.3\% of the classified corpus). The corpus grows at a compound annual
rate of 3.45\% (mean year-over-year growth 6.3\%, doubling time
11.3 years), peaking in 2025 with 112 records.
Non-negative matrix factorization extracts 5 latent topics over a
500-feature vocabulary, offline deterministic embeddings place every
title, abstract, and (when available) full text in a shared vector space, and
citation-network analysis exposes the corpus's internal structure (8,772
intra-corpus edges across 2204 nodes, 1377 communities,
graph density 0.18\%). Of 38,802 total outgoing
references, 22.6\% resolve to another record inside the corpus.
Abstract coverage stands at 55.5\%, open-access status is known for
14.4\% of records, and 40.9\% have a direct PDF link. An optional,
LLM-gated knowledge-graph stage scores the 6 hypotheses explored against
the evidence. This run produced 18 publication-quality figures.
Every domain-specific value in this manuscript — the search term, keyword set, engine
roster, subfield taxonomy, and hypotheses — is injected from a single configuration file
and the pipeline's own outputs; re-targeting the configuration re-targets the entire
paper. The result is a reusable architecture for living literature reviews:
continuously re-runnable, evidence-bound syntheses for any topic.
Keywords: modafinil, meta-analysis, literature retrieval, bibliometrics, record de-duplication, full-text mining, document embeddings, citation network, topic modeling, entity extraction, wakefulness, cognitive enhancement, reproducible research
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Associated artifacts
GitHub release: v0.1.0 (https://github.com/docxology/template_literature_meta_analysis/releases/tag/v0.1.0)
DOI: https://doi.org/10.5281/zenodo.20931964
Zenodo: https://zenodo.org/records/20931964
PDF SHA-256: 412d4fcf4b0c2e14fb950f9080f107d81fd9a90dfdf216b9161a13833eff62ff
Overview source: Curated paper metadata.
Methods and contributions
Read the source for the full argument, qualifications, and evidence.
Findings and contributions
- The live run retrieved and de-duplicated a corpus of 2302 modafinil records spanning 2000-2026.
- In the retrieved corpus (2000–2026), modafinil publications grow at a CAGR of 3.45%, doubling every 11.3 years, with a peak of 112 publications in 2025.
- Clinical Sleep is the largest subfield, at 64.3% of the classified corpus.
- The citation network has 2204 nodes, 8,772 edges and 1377 communities, with 22.6% of outgoing references resolving inside the retrieved corpus.
- The author notes the corpus is a bounded sample: a 1,000-per-engine cap applied and Semantic Scholar was rate-limited, returning zero records.
Methods
- Multi-engine literature retrieval across 7 engines with graceful degradation — Dispatches the 'modafinil' query to arXiv, OpenAlex, Semantic Scholar, Crossref, PubMed, SovietRxiv and ChinaRxiv; unavailable engines report skipped without aborting.
- Canonical-identifier de-duplication and keyword relevance filtering — Merges records by DOI > arXiv ID > Semantic Scholar ID > OpenAlex ID > title digest, keeping the most complete version, then filters by relevance keywords and start year 2000.
- Keyword-based 6-bucket subfield classification and growth metrics — Classifies records into Clinical Sleep, Cognition, Pharmacology, Psychiatry, Safety and Neuroscience and computes year counts, CAGR and doubling time.
- TF-IDF (500 features) + NMF topic model and TF-IDF/SVD embeddings — Builds a 500-feature TF-IDF representation of titles/abstracts, extracts 5 NMF topics, and embeds texts with offline deterministic TF-IDF/SVD.
- Intra-corpus citation network and config-driven token-injected manuscript — Builds a citation graph with community detection; all manuscript numbers are injected from a single config file and pipeline outputs with fixed seeds.
Summary sources: Paper metadata and evidence · Extracted source text.
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Citation
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