What is Clinical Battle Royale?
Clinical Battle Royale is a research feature inside the DeepCura clinical AI workspace that answers a clinical question by running four frontier AI models in parallel — Claude Opus 4.7, GPT-5.5, Gemini 3 Pro, and Grok 4 Fast — then ranks their answers with a blind tournament of 18 independent AI judgments.
It is built for clinical questions where a single AI answer is not enough: drug dosing in renal impairment, comparative effectiveness of two therapies, the latest guideline-recommended workup, and similar evidence-driven questions where you want multiple second opinions before deciding.
How It Works (in 60 seconds)
Four frontier AI models answering the same clinical question simultaneously. Each column shows the model name, the research tools it called (PubMed, Scholar, DailyMed), and a structured clinical answer beginning with the Bottom line.
- You ask a clinical question. Free text. Example: "In a 72-year-old with CrCl 28 mL/min and atrial fibrillation, is apixaban or warfarin preferred for stroke prevention?"
- Four AI models receive the question at the same time, with identical instructions and access to four research tools (PubMed, Google Scholar, DailyMed/FDA drug labels, and web search).
- Each model produces a structured answer with a Bottom line, evidence bullets with citations, dosing detail, contraindications, special populations, and a "What would change this answer" section.
- The system runs an 18-judgment blind tournament. The four answers form six unique pairs, and three different AI judges grade each pair on a five-dimension clinical rubric. Judges don't know which model produced which answer.
- You see the final ranking, the per-pair winners, every judge's written verdict, and every PubMed/Scholar/DailyMed search each model ran.
Where to Find It
Open any patient or general session in DeepCura Chat. In the workspace, switch the active tab to Clinical Battle Royale (the tab beside DeepEvidentia Chat). Type your question and submit. The four-column response view appears within a few seconds.
The Four Models
- Claude Opus 4.7 — Anthropic. Strongest long-context reasoning; best at synthesizing multiple sources into a structured clinical answer.
- GPT-5.5 — OpenAI. Broad medical training corpus; reliable structured output and well-formatted citations.
- Gemini 3 Pro — Google DeepMind. Largest context window; strongest multi-document synthesis.
- Grok 4 Fast — xAI. Real-time web grounding; the fastest agent in the panel — useful when an answer hinges on a recent FDA safety communication or guideline update.
The Four Research Tools (Every Model Uses Them)
- PubMed / MEDLINE — primary peer-reviewed literature via the NLM Entrez API. Models are instructed to prefer RCTs and systematic reviews.
- Google Scholar — society guidelines (ACC/AHA, IDSA, ASCO, NICE, USPSTF), consensus statements, and preprints.
- DailyMed — FDA-approved Structured Product Labels. Mandatory whenever the question mentions a specific drug or the model plans to recommend one.
- Web search — reserved for FDA safety communications, hospital protocols, and news-grounded questions.
The Five-Dimension Rubric (How the Judges Grade)
Inside a single pair's verdict. The top consensus row collapses what the three judges agreed on across the five dimensions. The three judge cards below show the individual scoring and written rationale — including dimensions where each judge thought the loser was actually stronger.
| Dimension | What earns a high score |
|---|---|
| Evidence Quality | RCTs, systematic reviews, current guidelines, FDA labels; recent enough for the specialty. |
| Clinical Accuracy | Doses match the FDA label; indications, contraindications, and mechanisms correct. Any single wrong drug dose drops this dimension to a score of 3 or less. |
| Completeness | Dose + route + frequency + duration, renal/hepatic adjustment thresholds, special-population coverage, drug interactions. |
| Reasoning Transparency | Tool-grounded reasoning, evidence-level tags, explicit "what would change this answer", confidence statement. |
| Citation Hygiene | Every clinical claim has a [N] reference; the Sources list matches; citations resolve to real, retrievable sources. |
How the Ranking Is Calculated
The tournament view after all judging completes. Top section: six pair-level cards. Bottom section: the Final Standings — a single-dimensional ranking of all four models produced by Bradley-Terry aggregation across the 18 judgments.
Four models produce six unique unordered pairs. Three judges grade each pair (two non-participating models plus a separate Claude judge call with randomized A/B order). That is 6 pairs × 3 judges = 18 independent judgments per question.
The wins matrix is then aggregated using the Bradley-Terry model — a 1952 statistical method for ranking competitors from paired-comparison outcomes. It is the same family of methods used for chess Elo ratings and the LMSYS Chatbot Arena LLM leaderboard.
What a Battle Royale Answer Contains
Each of the four answers follows the same structured format:
- Bottom line — 1–3 sentence direct clinical answer with specific intervention, dose, route, frequency, duration where applicable.
-
Evidence — 3 to 7 bulleted findings, each cited as
[N]with evidence-level tags (e.g., "RCT, n=2,135", "guideline, ACC/AHA 2023, Class I LoE A"). - Dosing / procedure detail — FDA-label dosing, renal/hepatic adjustments, CYP and P-gp interactions.
- Caveats and contraindications — including black-box warnings quoted verbatim from the FDA label when applicable.
- Special populations — pregnancy, pediatric, elderly, renal, hepatic, immunocompromised. If the sources don't cover a population, the answer says so explicitly.
- Disagreement with the user's framing — if the question contains a premise the evidence contradicts.
- What would change this answer — specific findings or lab values that would flip the Bottom line.
- Confidence — high / moderate / low with justification.
-
Sources — numbered list matching every
[N]; FDA labels include the last-updated date.
Credit Cost
- 8 credits — initial four-model fan-out (produces all four answers).
- 4 credits — run the judging tournament on top of the four answers.
- 4 credits — each follow-up turn in the same Battle Royale conversation.
Credits are part of every DeepCura subscription. The standard Pro plan includes more than enough credits for typical research and decision-support use; heavy researchers can purchase add-on credit packs from Settings → Billing.
When to Use Battle Royale (vs. DeepEvidentia or Standard Chat)
- Use Clinical Battle Royale when you want multiple independent AI second opinions on a clinical question and a ranked, source-grounded comparison — especially for drug dosing in special populations, comparative effectiveness, or any question where you need an audit trail.
- Use DeepEvidentia when you want to filter and chat against a specific curated set of medical journals — e.g. "search only the cardiology high-impact journals I selected for this question."
- Use Standard Chat for fast everyday questions where one AI response is enough — documentation, ICD-10 lookups, note edits, summarization.
Frequently Asked Questions
Is Clinical Battle Royale HIPAA compliant?
Yes. Battle Royale runs inside the same compliant environment as the rest of the DeepCura clinical workspace. All paid plans operate under a signed BAA with end-to-end encryption, and no patient data is used to train any of the four underlying models.
Can I share patient identifiers in a Battle Royale question?
Yes — you can ask patient-specific questions inside Battle Royale on a paid plan. As a clinician best practice, only include the clinical details (age range, comorbidities, labs, current medications) that are necessary to answer the question. Avoid names, MRNs, and other direct identifiers when the clinical context alone is enough.
Can I see the actual research each model did?
Yes. Every PubMed query, Google Scholar query, DailyMed lookup, and web search is logged in the session and visible per model. You can see the exact search string each model used, what was returned, and which results were cited in the final answer.
Can I follow up on a Battle Royale answer?
Yes. Each follow-up turn is sent to all four models in parallel and re-judged, so the panel stays consistent across the conversation. Each follow-up costs 4 credits.
What if the four models disagree?
This is the most useful case for Battle Royale — disagreement is surfaced explicitly. The per-pair judging breaks down which model the judges preferred on each of the five rubric dimensions, and the Bottom-line answers can be compared side by side. Where the underlying sources actually disagree, the answers will too — and you'll see exactly where.
Does Battle Royale replace clinical judgment?
No. Battle Royale is a decision-support and research tool, not a substitute for clinical judgment. The clinician remains the decision-maker and the legally responsible party. The structured "What would change this answer" section in every response is specifically designed to help map the AI analysis to the actual patient in front of you.
Which model "wins" most often?
It varies by question type. Different frontier models lead on different domains — long-context reasoning, multimodal inputs, web-grounded recency, citation hygiene. The point of running all four in parallel is precisely that no single model is reliably best across every question.