Fifteen Years, One Mission: Innovative, Inspirational, and Impactful Discoveries
Bibliographic record
Abstract
Recommendations F ifteen years ago, the American Chemical Society (ACS) introduced ACS Medicinal Chemistry Letters as a new means to rapidly report new findings in medicinal chemistry.In the inaugural issue of ACS Medicinal Chemistry Letters, the journal's founding Editor-in-Chief, Dennis Liotta, invited readers to use the journal as a mechanism to stay up to date with the fast-paced and ever-evolving field.In his editorial, Prof. Liotta stated he was "committed to making it the premier international journal for rapid communication of cutting-edge studies that span all areas of medicinal chemistry", a sentiment he echoed in the ten-year anniversary issue.When the journal's second Editor-in-Chief, Kelly Chibale, took the reins in 2023, he continued this legacy of commitment and looked to further expand the global reach and inclusivity of the journal.Under their leadership, the journal has risen to meet Prof. Liotta's original goal of being a leading journal for disseminating cutting-edge results.In addition to being a vehicle for timely research articles, the journal has introduced Patent Highlights and Innovations and also publishes highly relevant Microperspectives and Viewpoints that allow experts to provide insight into the many facets of the field.In celebration of the 15th anniversary of the founding of ACS Medicinal Chemistry Letters, the Early Career Board would like to take this opportunity to recognize the continued efforts from the members of the advisory, editorial, and early career boards�as well as our reviewers�who have helped shape the journal over the years.Of course, an essential component to the success of the journal has been the authors.Throughout the years, ACS Medicinal Chemistry Letters has published >3,400 articles from authors in >50 countries.In celebration of these authors, we have assembled this Collection of some of the most influential articles from each of the last 15 years.Reflecting the broad scope of the journal, these articles cover a wide range of subjects, including compound design and optimization, drug delivery, and pharmacology.While this is only a small sampling of the outstanding science that can be found in ACS Medicinal Chemistry Letters, these articles capture the translational
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.026 | 0.060 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.025 | 0.027 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.014 | 0.024 |
| Insufficient payload (model declined to judge) | 0.044 | 0.025 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".