Data & Figures

Reads intrinsic vs. display pixel dimensions to verify figure DPI requirements.

Converts a CSV paste into a LaTeX tabular or bmatrix environment.

Generates Okabe-Ito or Viridis-based palettes with hex codes for accessible figures.

Renders an SVG to a high-resolution TIFF — right in your browser, no upload needed.

Simulates how a figure looks when printed in black and white.

Calculates a calibrated scale bar and overlays it on a microscopy image.

Extracts tabular data from unstructured text and formats it as a table.

Generates a graphical abstract layout description from your abstract text.

Checks figure captions for panel labels, sample size, error bar definitions, and statistical test mentions.

Flags numbers with inconsistent significant figures and mismatched value–uncertainty precision.

Simulates deuteranopia and protanopia for your figure colors and flags indistinguishable pairs.

Auto-detects delimiters and outputs a fixed-width plain-text table or LaTeX tabular.

Replaces flagged indistinguishable color pairs with accessible Okabe-Ito or Viridis alternatives.

Drafts missing figure caption elements — panel labels, sample size, error bar definitions, and statistical test mentions.

Rounds all values in a results section to a consistent number of significant figures and aligns value–uncertainty precision.

Provides targeted instructions and code snippets to upsample a figure to meet journal DPI requirements.

Paste raw numeric data to instantly calculate mean, SD, SEM, and 95% confidence interval — with results formatted ready to paste into figure legends.

Convert raw p-values to APA style (p = .023), exact notation, or threshold notation (p < 0.05) — paste multiple values at once and get formatted output.

Visual table builder that generates publication-quality booktabs LaTeX — add rows and columns interactively, set headers, and copy the ready-to-use LaTeX code.

Enter R², Cohen's d, Cohen's f, or η² to get a plain-English interpretation with the standard magnitude label (small / medium / large) and context for academic writing.

Upload a chart image and click on data points to extract their approximate values — a browser-based plot digitiser that exports your clicked coordinates as CSV.

AI recommends the right statistical test for your data — describe your study design (groups, data type, distribution) and get a justified recommendation with references.

AI cross-checks your Results section text against the figures and tables you describe — flags mismatches, missing references to figures, and unsupported claims.