Citation laundering
A real paper is cited for a claim it does not make. General reviewers see a DOI and move on.
Scientific data annotation
Scientific AI Evaluation and Expert Training Data
Scientific models and research agents fail by overclaiming. They cite a paper that does not support the sentence, collapse a method’s assumptions, or present a plausible mechanism as if it were established.
We are not a freelancer marketplace or traditional staffing company.
What is scientific data annotation
Scientific data annotation is discipline-specific labeling, scoring, or authoring of research artifacts so an AI system can be trained or evaluated against a field’s methods, not generic STEM literacy. A biologist is not a substitute for a chemist on a synthesis question.
What scientific expert review is for
Technical buyers usually already have general STEM-literate raters. The gap is narrower and more expensive: people who can judge a claim inside a named field. A biologist is not a substitute for a chemist on a synthesis question. A statistician is not a substitute for a materials scientist on a characterization claim.
The work is therefore specified by discipline, methods familiarity, and sometimes by a particular literature, not by “science” as a single bucket.
Potential experts
Example profiles include PhD researchers, postdoctoral researchers, industry scientists, biologists, chemists, bioinformaticians, biochemists, physicists, materials scientists, and statisticians. These are examples of profiles that may be sourced, not a roster.
Typical work
- Scientific reasoning evaluation
- Research evaluation
- Literature synthesis evaluation
- Benchmark construction
- Reference answers
- Experimental reasoning
- Research agent evaluation
- Expert adjudication
Failure modes worth scoring
Method collapse
Assumptions of an assay, model, or statistical test are dropped while the vocabulary stays intact.
Overconfident synthesis
Conflicting results are averaged into a single tidy paragraph.
Protocol fantasy
An experimental plan is internally consistent and still physically or ethically implausible.
Frequently asked questions
- Do you staff undergraduate STEM raters as experts?
- Only if the brief asks for that level. Most scientific evaluation programs that contact us need graduate-level or industry-scientist judgment.
- Can one PhD cover a broad benchmark?
- Broad benchmarks usually need a panel. A single discipline expert will systematically miss adjacent-field errors.
- How do you handle unpublished client science?
- Treat it as confidential project data. Prefer client-controlled environments and minimize what reviewers need to see.
Request scientific expert capacity
Share the profession, specialty, experience, location, headcount, hours, duration, and project description. We assemble the expert capacity.
- Need 25 licensed nurses for a clinical AI evaluation
- Need 15 attorneys in a specific practice area
- Need 20 PhD scientists for benchmark creation
- Need 30 senior software engineers for code evaluation