How

AI Tools for Scientific Experiment Design and Data Planning

Vendor pages document upload limits, plan features, and data controls for AI-assisted experiment planning, but not scientific accuracy for a particular study.

Sources checked 2 Oct 2026

AI tools can help you structure variables, draft data-collection plans, work through sample-size questions, and organize research records, but vendor documentation does not establish that their suggestions are correct for a particular study. OpenAI, Anthropic, and Google document features, limits, and safeguards; the pages reviewed do not supply a scientific-design benchmark for ChatGPT, Claude, or Gemini. Chat Picker has not tested the assistants and has no test results, scores, rankings, survey data, or user statistics of its own.

What the vendors document

As read on October 1, 2026, OpenAI's Plus help page lists Plus at $20 per month. Anthropic's pricing page lists Claude Pro at $20 per month, or $17 per month with annual billing and $200 up front. Google's US plans page lists Google AI Pro at $19.99 per month. These are prices, not measures of output quality.

Accepted-file rules matter when you work with protocols, spreadsheets, and data dictionaries:

ChatGPT: OpenAI's File Uploads FAQ, read October 1, 2026, says uploads are available on Free and paid plans. Each file has a 512 MB hard limit; CSV files and spreadsheets are capped at about 50 MB. Free users have three uploads per day and five files per project; Go and Plus projects allow 25 files.
Claude: Anthropic's file-upload page, read October 1, 2026, lists 500 MB per chat file and 30 MB per project file. XLSX requires code execution and file creation. Claude analyzes text and visual elements in PDFs of 100 pages or fewer, but processes only text for PDFs from 101 to 1,000 pages.
Gemini: Google's file-upload help page, read October 1, 2026, lists up to 10 supported files per prompt, subject to availability, 2 GB per video, and 100 MB for each other supported file. Paid plans can raise feature limits, and the web app can create customizable charts from uploaded spreadsheets.

Data controls answer different questions. OpenAI's file-upload FAQ, read October 1, 2026, says chats remain in the account until deletion and uploaded files follow the relevant chat retention period. OpenAI's pricing page, read the same day, offers a training opt-out on Free, Go, Plus, and Pro. Anthropic's pricing page, also read October 1, 2026, lists opt-outs for Free, Pro, and Max and says Team is not trained on by default. Google's US plans page gives no app token figure and states no training setting, so Chat Picker leaves both items unverified.

The accuracy notes are explicit. OpenAI's truth help page, read October 1, 2026, says ChatGPT may be wrong while sounding confident and should be treated as a first draft whose quotations, data, technical details, and references require checking. Anthropic's incorrect-responses page, read the same day, says not to rely on Claude as the only source of truth and to inspect original sources because a synthesis can omit context.

The policy pages, also read October 1, 2026, add review requirements. OpenAI's usage policies prohibit automated high-stakes decisions in sensitive areas without human review. Anthropic's Usage Policy calls for relevant human expertise in elevated-risk uses and disclosure of AI involvement for direct user-facing outputs. Google's Gemini safety guidelines say outputs are probabilistic, may reflect training-data limits or overgeneralizations, and are evaluated in context, including scientific applications.

What the documentation cannot tell you

The pages cannot tell you whether an assistant has caught a confounding factor, chosen a defensible statistical method, preserved units, handled missing values correctly, or kept a citation within its source context. Those judgments depend on your field, protocol, files, current limits, and account settings. The vendor pages provide no common scientific-design validation result for these assistants. The previous version's unsourced statistics and test results have been removed.

How to check it yourself

Run the same defined tasks on each assistant, using non-sensitive test material first:

Build the variable scaffold. Upload the protocol and ask: "Using the attached protocol, create a table containing each variable's name, role, unit, allowed values, missing-value code, and source sentence. Mark ambiguity and do not infer." Check that every row traces to the protocol. Record corrections and unresolved terms.
Check sample-size reasoning. Upload the protocol and pilot dataset. Ask: "Calculate the sample size for the primary outcome using only the alpha, power, effect-size, allocation-ratio, and attrition inputs stated in the attached files. Show each formula, value, and unit; stop if an input is missing." Recalculate it in validated statistical software. Record assumptions and discrepancies.
Convert the protocol into a schema. Upload the collection protocol and ask: "Create a metadata schema that maps each collected field to a variable, preserves the source wording, flags ambiguous labels, and adds validation checks. Do not invent fields." Check for lost units, inconsistent codes, and fields without a source. Record unresolved mappings.
Run a virtual pilot. Upload the protocol, draft data dictionary, and analysis plan. Ask: "Simulate only the data-generation and analysis steps supported by the attached files. List assumptions, expected fields and units, and failure checks. Identify steps requiring physical measurement and do not present simulated values as observations." Record every step that still needs a physical or domain-specific check.
Draft a notebook audit trail. Upload the protocol, data dictionary, analysis script, and draft entry. Ask: "Create an audit-trail entry that preserves source file identifiers, software versions, deviations, and approval fields. Mark missing facts as missing and append a change log." Check for invented metadata or altered source facts. Record unresolved fields and reviewer actions.
Cross-check the output. Supply the prior answer, source protocol, analysis plan, and domain guidance. Ask: "Trace every quantitative claim to a supplied source, recompute what can be recomputed, and list contradictions, unsupported citations, and decisions requiring domain-expert review." Independently use validated domain or statistical software. Record mismatches and their disposition after expert review.

Which rows of the comparison matter

Open the Claude, ChatGPT and Gemini matrix and read these rows first:

Free plan, Main paid plan, and Heavy-use plans for access and stated capacity.
Context window in the app and How usage limits are described for documented capacity limits.
Training on your chats for available data controls.
Team plan for shared governance, billing, and documented defaults.

Check the vendor link and read date beside every figure. A Not verified cell means the vendor page did not settle the point; it does not mean “no.” Use the matrix to compare documented terms, then run your own protocol-level check before relying on an answer.