Models
A mixture of models, cross-checked.
Every frontier model (Claude, GPT, Gemini, Mistral, Grok) alongside our own, routed per sub-task and made to check each other. No single-model bias.
Explore Science vs ChatGPT
ChatGPT will critique a pasted paper in seconds. Explore Science is an AI co-scientist built only for science: a chat grounded in your whole body of work, a deep review that puts a Calibre score on the manuscript, and every reference verified.
The short answer
Choose Explore Science when you want a scored, defensible read on the science: a Calibre score across eight categories, every reference checked against live databases, and a chat that already knows your manuscripts, reviews and scores. Choose ChatGPT when you want a fast generalist for drafting, coding, or a ten-second sanity check. The models overlap, so the difference sits elsewhere: a general chat starts each session from nothing and answers in one pass, while Explore Science spends up to 2 hrs letting frontier models and our in-house Explorer One cross-check each other against your research history. The flaws that sink a paper rarely surface in a single fast pass.
Compared July 2026 · from ChatGPT's own published materials
Choose Explore Science when
- Calibre scores the manuscript out of 100 across eight categories against a published rubric, from day one, before the paper has a single citation.
- Up to 2 hrs of checking per manuscript, with frontier models and our in-house Explorer One cross-checking each other, so no verdict rides on one model's first answer.
- Every reference in your bibliography is checked against live scholarly databases, and we flag the ones that do not resolve or do not support the claim attached to them.
- Each paper lives in a workspace where every revision is scored, so you can see which categories moved between drafts.
- Rosa, the co-scientist chat, is grounded in your paper, its review and your wider body of work, with sharing built in for co-authors and your lab.
Choose ChatGPT when
- Answers in seconds. For a quick rephrase or "is this paragraph clear", it is faster and the right tool.
- Does far more than review: writing, coding, data analysis, web browsing, image generation and agent workflows.
- Researchers at participating institutions can get it free through OpenAI's ChatGPT for Academic Researchers programme, announced 29 July 2026, with frontier models, expanded deep research and no training on their data.
- Its deep research mode browses and synthesises the open web into a cited report with working links, which Explore Science does not do.
- Business and Enterprise workspaces are not trained on by default, which suits teams standardising on one assistant.
Side by side
| Capability |  | ChatGPT |
|---|---|---|
| What it is | An AI co-scientist built only for science: chat, review and collaboration | A general assistant that reviews a paper only when you ask |
| TurnaroundPer manuscript review | Up to 2 hrs of checking, emailed when it lands; no chat window to sit in front of | Seconds to a few minutes per reply |
| Review engine | GPT is one of five frontier models here (with Claude, Gemini, Mistral and Grok) plus our in-house Explorer One, cross-checked against each other | One vendor's model family; reasoning and deep research add steps, but nothing adjudicates between different models |
| Quality score | Calibre: a score out of 100 across eight categories, against a public rubric | Give it a rubric and it will score against it, but the numbers are not calibrated and do not compare between papers or drafts |
| Reference checking | Every reference checked against live databases; non-resolving and unsupported ones flagged | No built-in check of your bibliography; add-on apps such as Consensus and Scite bring scholarly search into ChatGPT, run by you, reference by reference |
| Revisions | Each draft scored and compared with the last, in one workspace | Projects, memory and local multi-folder projects on desktop keep drafts together; comparison stays conversational, with no scored diff |
| Paper-grounded chat | Rosa answers with your manuscript, its Calibre report and your earlier papers already loaded, so you never paste context in | General chat; can be scoped to a paper in a Project, but not grounded in your research history |
| Free access for academics | No academic programme; free tier only | ChatGPT for Academic Researchers: free frontier access for researchers at selected institutions, plus up to four collaborators |
| Breadth | Scientific review and collaboration only | Writing, code, data, web, images, agents |
| Pricing | Free to start; $49 for a single review with no subscription; $99 or $199 a month with a usage allowance | Free; $8 to $200/mo individual; Business from $20 per seat; Enterprise on quote; free for accepted academic researchers |
90% rate a review on par with or better than the human peer review they have had.
Two in three rate it better. From 304 head-to-head ratings by researchers who had received peer review on the same paper. These are our own users, self-reported, which is worth knowing when you weigh them.
Depth
Why a thorough review takes the time it takes.
Most tools optimize for speed. Explore Science runs the engine we built to conduct original research autonomously, and points it at your manuscript: it reads recent literature in your field, checks every reference, and works through the paper the way a careful reviewer does.
The time is the method, not an overhead on it.
How a paper is scoredTime spent thinking about your paper
How long a review actually takes
Single-pass LLM
~2 min
Other AI reviewers
5 to 20 min
Human peer review
(active reading time)
~30 min
Explore Science
up to 2 hrs
Industry observation; self-reported vendor figures; Publons peer-review time survey, 2018.
The engine
What actually reads your paper.
Three pieces of the architecture do the work behind every review.
Agents
Scientific agents that reason like the field.
Dozens of specialised agents work each review in parallel, each tuned to one dimension of analysis, spawning more when a section needs them.
Infrastructure
An in-house science stack.
Memory that holds your paper in context for the whole review, live verification of every citation, and novelty assessment. Built over years of autonomous science.
The citations it invents look real
Fabricated references are a documented failure mode of general chatbots on scientific text, and detecting them reliably is still an open research problem. ChatGPT can now reach scholarly literature: Consensus and Scite ship apps inside it, and its web and deep research modes return real links. What none of that does is take your bibliography and test it, entry by entry, against a structured database. You drive that yourself, one reference at a time, and the citation you never think to question is the one that gets through.
Explore Science checks every reference against live scholarly databases and flags any that do not resolve or do not support the claim attached to them. That catches the error an editor would otherwise catch for you, after rejection.
A number you can defend
Ask ChatGPT to grade a manuscript against a rubric and it will return numbers. The question is what they mean: published work on rubric-based grading with these models finds inflated scores and compressed distributions, with structure and fluency rewarded over analytical depth and originality. Two papers scored in two sessions are not comparable, and neither are two drafts of the same paper.
Calibre is fixed, published, and applied the same way every time, so an 82 in March and an 82 in July mean the same thing. That is what lets you cite it in a rebuttal, take it into a supervisor meeting, or use it to decide whether a paper is ready to go out.
Common questions
Will ChatGPT train on my unpublished manuscript?
On Free, Go, Plus and Pro, OpenAI uses conversations to improve its models unless you switch it off in Data Controls; users in the EEA, UK and Switzerland are excluded by default, and even opted-out chats are retained for around 30 days for abuse review. Business, Enterprise and academic-researcher workspaces are not trained on by default. Explore Science does not train models on user manuscripts at all, and you can permanently delete any paper from your workspace.
Can ChatGPT check my reference list?
Partly, and only if you drive it. Add-on apps such as Consensus and Scite let it search scholarly databases from inside a chat, so you can look references up one at a time, but nothing validates a whole bibliography or tells you which entries fail to support the claim they are attached to. Explore Science runs that pass on every reference in the paper.
What if I only have one paper to review?
Buy a single review for $49, with no subscription: one full-depth review, scored on Calibre, with DOI-verified references. The $99 and $199 monthly plans are for people running several manuscripts, or the same manuscript through several drafts.
Can ChatGPT track changes between drafts of my paper?
Up to a point. Hold both drafts in a Project, or in a local project folder on the desktop app, and it will compare them in conversation, but there is no scored, rubric-anchored diff between versions. Explore Science keeps a paper in one workspace, scores every revision, and shows which categories moved.
Claims about ChatGPT reflect its own published materials; everything about Explore Science reflects what the platform does today. Sources: ChatGPT, OpenAI pricing, ChatGPT for Academic Researchers (OpenAI, 29 July 2026), How your data is used to improve model performance (OpenAI), ChatGPT release notes, Scite ChatGPT app, Consensus MCP and ChatGPT app, CiteCheck: retrieval-grounded detection of LLM citation hallucinations, Evaluating ChatGPT's reliability, validity and bias in automated academic grading. Something out of date? and we will fix it.
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