Original research · 2026-07 edition

AI SEO Statistics: Burn Surgeons (2026-07 edition)

40 questions · 120 AI responses · 3 models · measured 2026-07-06

See how AI talks about YOUR businessFull data table

The question bank

The questions we tested — sampled from real buyer journeys in burn surgeons.

Each model answered every question once, same wording, same day. These are the prompts behind every percentage on this page.

I accidentally spilled boiling water on my leg and it's blistering, should I see a burn surgeon or just go to urgent care?
What is the difference between a general surgeon and a specialized burn surgeon for skin grafts?
How do I know if a burn is deep enough to require surgery?
What questions should I ask a burn specialist about laser scar revision?
Are there specific burn surgeons who specialize in facial reconstruction after a fire?
How much does a skin graft procedure typically cost without insurance?
What are the signs of infection in a second-degree burn that mean I need a specialist?
Can a burn surgeon help with old contracture scars that are limiting my hand movement?
Show all 40 questions
Is it better to go to a dedicated burn center or a regular hospital for a chemical burn?
How long is the recovery time after a major skin graft surgery?
What qualifications should I look for when choosing a surgeon for pediatric burn care?
Does insurance usually cover reconstructive surgery for burn scars if it's for range of motion?
My burn is turning white and I can't feel pain there, is that an emergency?
How do I find a burn surgeon who has experience with high-voltage electrical injuries?
What are the red flags to watch out for when looking at a burn clinic's success rates?
Can a burn surgeon improve the appearance of hypertrophic scarring from a year ago?
What's the protocol for transferring a patient from a small hospital to a regional burn unit?
Are there non-surgical options a burn specialist might recommend before suggesting a graft?
I have a grease burn that won't stop oozing, do I need a specialist or just antibiotics?
How do burn surgeons manage pain during the debridement process?
What's the average wait time to see a burn reconstructive specialist for a consultation?
Should I see a burn surgeon for a friction burn from a motorcycle accident?
What are the latest advancements in spray-on skin and which surgeons offer it?
How many years of fellowship training does a board-certified burn surgeon need?
Can a burn surgeon help with nerve damage caused by a deep thermal injury?
What should I bring to my first appointment with a burn reconstruction specialist?
Is it worth traveling to a major city for a burn center if my local hospital has a general surgeon?
How do I compare the complication rates of different burn surgeons in my area?
What are the risks of waiting too long to get a skin graft for a deep burn?
Do burn surgeons also handle smoke inhalation complications or is that a different doctor?
My child has a small but deep burn on their palm, do they need a pediatric burn specialist?
What is the success rate for skin substitutes versus traditional autografts?
Can a burn surgeon help with pigment loss after a healed burn?
How do I verify if a surgeon is a member of the American Burn Association?
What kind of follow-up care is required after being discharged from a burn unit?
If a burn is circular and goes all the way around my arm, why is that considered a surgical emergency?
Are there specific burn surgeons who focus on radiation burns from cancer treatment?
What's the difference between an outpatient burn clinic and an inpatient burn ward?
How do I know if my burn surgeon is using the most modern grafting techniques?
Will a burn surgeon work with physical therapists as part of the recovery plan?

Model by model

15-point average divergence: which AI you ask changes the answer.

The divergence index is the average gap between the most and least likely model per behavior. Higher = the models disagree more about burn surgeons buyers.

Behavior rates across 40 burn surgeons buyer questions, 2026-07 edition. Last column: average across models.
ChatGPTClaudeGeminiConsensus
Recommends hiring a professional70%60%50%73%
Suggests DIY first18%8%8%83%
Names specific providers0%8%3%93%
Gives price or cost info3%3%3%100%
Tells to check reviews5%5%0%93%
Tells to verify credentials18%20%15%78%
Mentions case studies / portfolio8%5%3%88%
Mentions local proximity28%20%15%68%
Gives selection criteria33%33%28%73%
Warns about red flags5%5%3%93%
Asks a clarifying question70%70%0%10%
Recommends multiple quotes8%10%0%85%

By model

How each assistant handled Burn Surgeons questions.

Reading the 120 answers model by model shows how differently the three assistants treat the same burn surgeons questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 70% (ChatGPT) down to 50% (Gemini), a 20-point gap on an identical question set.

Across the 40 burn surgeons answers it produced, ChatGPT recommended hiring a professional in 70% of them and suggested a DIY approach first 17.5% of the time. It named a specific provider in 0% of answers (about 0 distinct providers per answer) and included price or cost information 2.5% of the time. ChatGPT asked a clarifying question before answering in 70% of cases, warned about red flags or scams in 5%, and told the buyer to verify credentials in 17.5%, averaging 441 words per answer. On the remaining cues it told the buyer to check reviews in 5%, pointed to case studies or a portfolio in 7.5%, and framed the choice around local proximity in 27.5%; a selection-criteria checklist appeared in 32.5% of its answers and a recommendation to gather multiple quotes in 7.5%.

Across the 40 burn surgeons answers it produced, Claude recommended hiring a professional in 60% of them and suggested a DIY approach first 7.5% of the time. It named a specific provider in 7.5% of answers (about 0.2 distinct providers per answer) and included price or cost information 2.5% of the time. Claude asked a clarifying question before answering in 70% of cases, warned about red flags or scams in 5%, and told the buyer to verify credentials in 20%, averaging 288 words per answer. On the remaining cues it told the buyer to check reviews in 5%, pointed to case studies or a portfolio in 5%, and framed the choice around local proximity in 20%; a selection-criteria checklist appeared in 32.5% of its answers and a recommendation to gather multiple quotes in 10%.

Across the 40 burn surgeons answers it produced, Gemini recommended hiring a professional in 50% of them and suggested a DIY approach first 7.5% of the time. It named a specific provider in 2.5% of answers (about 0.1 distinct providers per answer) and included price or cost information 2.5% of the time. Gemini asked a clarifying question before answering in 0% of cases, warned about red flags or scams in 2.5%, and told the buyer to verify credentials in 15%, averaging 295 words per answer. On the remaining cues it told the buyer to check reviews in 0%, pointed to case studies or a portfolio in 2.5%, and framed the choice around local proximity in 15%; a selection-criteria checklist appeared in 27.5% of its answers and a recommendation to gather multiple quotes in 0%.

Taken together, ChatGPT is the assistant most likely to route a burn surgeons buyer to a professional (70%) and Gemini the least (50%). ChatGPT produced the longest answers, at 441 words on average. Specific providers were named most often by Claude (7.5%) — even there, roughly one answer in 13 carried a name.

Where they disagree

The behaviors where the choice of model changes the answer.

The divergence index for this study is 14.9 points — the average distance between the most and least likely model across the coded behaviors. The gaps below are where which assistant a burn surgeons buyer happens to ask matters most:

  • Asks a clarifying question: from 0% (Gemini) to 70% (ChatGPT) — a 70-point spread.
  • Recommends hiring a professional: from 50% (Gemini) to 70% (ChatGPT) — a 20-point spread.
  • Mentions local proximity: from 15% (Gemini) to 27.5% (ChatGPT) — a 13-point spread.
  • Suggests a DIY approach first: from 7.5% (Claude) to 17.5% (ChatGPT) — a 10-point spread.
  • Recommends multiple quotes: from 0% (Gemini) to 10% (Claude) — a 10-point spread.

The widest single gap — asks a clarifying question, 70 points — means a burn surgeons buyer can receive materially different guidance on the same question depending only on which assistant they happen to open, so any visibility strategy built on a single model's behavior describes only part of the burn surgeons market.

Where they agree

The points of near-consensus in Burn Surgeons.

On other behaviors the three models move almost in lockstep — the points of near-consensus for burn surgeons, where all three landed within a few points of each other:

  • Gives price or cost information: 2.5% across all three models.
  • Warns about red flags or scams: 2.5%–5% across all three (a 3-point spread).
  • Tells the buyer to check reviews: 0%–5% across all three (a 5-point spread).
  • Tells the buyer to verify credentials: 15%–20% across all three (a 5-point spread).

Measured question by question, the three assistants coded a response the same way most consistently on "gives price or cost information" (identical coding in 100% of questions) and least consistently on "asks a clarifying question" (10%).

Every behavior, measured

All twelve coded behaviors for Burn Surgeons, averaged across the three models.

The behaviors AI models reproduce most often for burn surgeons are recommends hiring a professional (60% on average), asks a clarifying question (46.7%) and gives selection criteria (30.8%); the rarest are gives price or cost information (2.5%), tells the buyer to check reviews (3.3%) and names a specific provider (3.3%). Each figure below is the share of a model's 40 answers in which the behavior appeared at least once, averaged across the 3 models with the full per-model range in parentheses:

  • Recommends hiring a professional: 60% on average (ChatGPT 70%, Claude 60%, Gemini 50%) — a 20-point spread.
  • Asks a clarifying question: 46.7% on average (ChatGPT 70%, Claude 70%, Gemini 0%) — a 70-point spread.
  • Gives selection criteria: 30.8% on average (ChatGPT 32.5%, Claude 32.5%, Gemini 27.5%) — a 5-point spread.
  • Mentions local proximity: 20.8% on average (ChatGPT 27.5%, Claude 20%, Gemini 15%) — a 13-point spread.
  • Tells the buyer to verify credentials: 17.5% on average (ChatGPT 17.5%, Claude 20%, Gemini 15%) — a 5-point spread.
  • Suggests a DIY approach first: 10.8% on average (ChatGPT 17.5%, Claude 7.5%, Gemini 7.5%) — a 10-point spread.
  • Recommends multiple quotes: 5.8% on average (ChatGPT 7.5%, Claude 10%, Gemini 0%) — a 10-point spread.
  • Mentions case studies or portfolio: 5% on average (ChatGPT 7.5%, Claude 5%, Gemini 2.5%) — a 5-point spread.
  • Warns about red flags or scams: 4.2% on average (ChatGPT 5%, Claude 5%, Gemini 2.5%) — a 3-point spread.
  • Names a specific provider: 3.3% on average (ChatGPT 0%, Claude 7.5%, Gemini 2.5%) — a 8-point spread.
  • Tells the buyer to check reviews: 3.3% on average (ChatGPT 5%, Claude 5%, Gemini 0%) — a 5-point spread.
  • Gives price or cost information: 2.5% on average (ChatGPT 2.5%, Claude 2.5%, Gemini 2.5%).

Trust signals

How well the models protect the burn surgeons buyer.

Beyond whether to hire, the rubric codes how carefully each assistant protects the burn surgeons buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 3.3% of answers on average. Verifying credentials or certifications appeared in 17.5%. Warning about red flags or scams appeared in 4.2%.

On structuring the decision, a selection-criteria checklist showed up in 30.8% of answers on average and a recommendation to gather multiple quotes in 5.8%. The single least-reproduced protective signal for burn surgeons is "tells the buyer to check reviews" at 3.3% on average — the clearest opening for content that supplies it, since the models are not yet reliably surfacing that guidance on their own.

Referral behavior

Do AI models name Burn Surgeons providers?

For service providers the decisive question is whether these systems name anyone at all. Across 120 burn surgeons answers, a specific provider was named in 3.3% of responses on average — roughly 0.1 distinct providers per answer. In practice the assistants behave far more as an explanatory layer than as a referral engine for burn surgeons: visibility comes from being the reasoning a model reproduces, not from being the named recommendation.

The question set

What these 40 Burn Surgeons questions cover.

The 40 questions behind every percentage on this page were drawn from real burn surgeons (healthcare services; buyer hiring decisions for this specific service) buyer journeys. Each was put to all 3 models once, with identical wording, so the rates above describe how the assistants handled this exact burn surgeons question set — not a general prior or a hand-picked subset. The full list is shown earlier on this page; the coded percentages are what those specific questions produced.

How to read this

A note on the numbers.

A percentage here is the share of a model's 40 answers in which the behavior appeared at least once — not a confidence score. Because each model answered every question exactly once on 2026-07-06, the figures describe this specific burn surgeons question set and snapshot rather than a general prior. The full protocol and coding rubric are documented in the study methodology.

Methodology

A controlled snapshot, documented end to end.

40 standardized buyer questions per industry, one response per model per question (ChatGPT (gpt-5-mini), Claude (claude-sonnet-5), Gemini (gemini-3-flash-preview)), collected 2026-07-06, coded against a fixed 12-behavior rubric with human QA. AI outputs vary with model version, location and time — figures describe this sample and window, and are refreshed each edition. Read the full methodology →