The Chemical Probes Portal – 2024: update on this public resource to support best-practice selection and use of small molecules in biomedical research
Bibliographic record
Abstract
The Chemical Probes Portal (www.chemicalprobes.org) is a free, public resource, based on expert-reviews, that supports the assessment, selection and use of small-molecule compounds that qualify as chemical probes. These high-quality reagents are essential for exploring the function of individual proteins in complex biological systems, such as cells and organisms, and for validating proteins as potential therapeutic targets. The use of reliable chemical probes accelerates protein annotation in basic biological studies and informs drug discovery. However, the use of low-quality compounds has historically led to erroneous conclusions in biomedical research, and experience shows that failure to follow best practice continues, an issue which the Portal aims to address. Here, we describe the latest updates to the Chemical Probes Portal in both content and functionality. The number of chemical probes and human protein targets covered has increased significantly, with improvements in the processes for obtaining expert reviews and user engagement. Moreover, new functionalities and enhanced tools have been introduced to better support biological researchers in selecting and using the best chemical probes for their studies.
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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 | 0.021 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.113 | 0.089 |
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".