ArticleMolecular informatics2026
MolScope: A Transparent Representation-Aware Workflow Toolkit for Reproducible Medicinal-Chemistry Triage.
Article in Molecular informatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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0 citing papers in PubMed.
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Authors and funding
1 author.
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Abstract
Medicinal-chemistry review is often built from disconnected notebooks, spreadsheets, and slide decks that hide structure-normalization choices and blur the boundary between measured observations and heuristic prioritization. MolScope is an open-source Python workflow toolkit that converts molecular structure collections and optional assay joins into a canonical chemistry table, category-aware summaries, and decision-ready report and picklist artifacts. The workflow makes representation policy explicit, preserves evidence provenance, and packages outputs as portable HTML, Markdown, and CSV bundles. Using frozen example datasets, we show reproducible end-to-end execution, auditable handling of salts, tautomers, stereo ambiguity, charge state, and one bounded round-review example for comparative campaign support.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.