research verification

Output that survives reviewer scrutiny.

The problem is not finding papers. The problem is trusting what the draft claims they support.

bottom line

Citations verified. Weak support surfaced. Unsupported claims stopped before reviewers see them.

01 // what it does

You direct. The engine verifies.

Define the domain. Provide the corpus. The engine checks citation support, maps contradictions, and pressures the draft before it reaches a reviewer.

Any scientific domain
1000s papers per corpus
every citation checked

Sources: PubMed, Semantic Scholar, or your own corpus. Evidence verified before delivery. Weak claims rejected early.

Fabricated references are not hypothetical. An analysis reported by Retraction Watch in May 2026 found them in about 1 in 277 PubMed-indexed papers from early 2026.

02 // verification pipeline

How it works

corpus ingestion Papers indexed by domain-specific ontology
→
support + contradiction check citations and evidence support inspected before output moves
→
independent critique domain critic attacks claims on mechanism, evidence, and feasibility
→
review-ready package only what survives moves forward for human review

A domain critic attacks mechanism plausibility, evidence strength, safety profile, novelty, and testability. Weak candidates are rejected before delivery.

[ submit claim ]
03 // case study: psychedelic medicine

1,538 papers. 21 candidate hypotheses. 1 survived verification.

A research team ran the complete psychedelic and ketamine antidepressant literature. The verification layer rejected most candidates. One survived with verified support.

the discovery: temporal stacking of mGlu2/3 antagonism after ketamine

Verdict: VIABLE
Mechanism: Sequential mGlu2/3 receptor antagonist administration 24-72h post-ketamine intercepts the declining neuroplasticity window, extending BDNF-TrkB-mTOR signaling
Evidence: Supported by 12 verified papers across behavioral pharmacology, receptor binding, and BDNF pathway studies

Cross-referenced papers rarely read together. The real value: unsupported ideas do not masquerade as conclusions.

04 // case study results

All 7 directions, 21 hypotheses

Case study results comparison
Direction Hypotheses Best Verdict Key Finding
mGlu2/3 + Ketamine Stacking 3 VIABLE Temporal stacking extends neuroplasticity window
5-HT2A Receptor Modulation 3 WEAK Partial agonist approach needs more specificity data
Muscimol + SSRI Interactions 3 WEAK Safety finding: serotonin syndrome risk flagged
Neuroplasticity Cascades 3 WEAK BDNF timing windows need dose-response data
Default Mode Network 3 REJECTED Mechanism too diffuse for actionable protocol
Gut-Brain Axis 3 REJECTED Insufficient mechanistic evidence for psychedelic link
Epigenetic Markers 3 REJECTED Too speculative for current evidence base
05 // unexpected value

It finds risks too.

case study bonus: drug interaction safety signal

The engine flagged a triple interaction: muscimol + trazodone + sertraline creating serotonergic excess. Emerged from combinatorial analysis across 1,538 papers — too diffuse for manual review.

Any domain. The engine catches contradictions and safety signals that fast synthesis flattens away.

what you gain

Adversarial critique from independent model families surfaces failure modes a single-model review can miss.

what it costs

Slower than a single-pass review. Requires a well-formed question.

06 // specialized domains

Verification by research domain.

Domain-specific corpora. Segment-tuned proof points. Same adversarial pipeline.

psychiatry

Psychedelics research

Ketamine, psilocybin, MDMA. 1,538-paper corpus.

 oncology

Immunotherapy research

Checkpoint inhibitors, biomarkers. 8,269-paper corpus.

 ai safety

Alignment research

Cross-architecture adversarial review. 744-paper corpus.

 clinical ai

Diagnostic AI research

SaMD validation, clinical decision support. 656-paper corpus.

 cardiology

Cardiovascular research

GLP-1, SGLT2, cardiovascular outcomes. Adversarial review.

 neurology

Alzheimer's research

Biomarkers, neurodegeneration, trial design. Citations verified. Contradictions surfaced.

 institutional

R&D institutions

Cross-model verification for R&D institutions.
07 // start

Run one claim through the pipeline.

Send the corpus and question. We confirm the review scope before work starts.

[ submit claim ]
other tracks //
grants // legal // clinical // compliance