BGPT: Create Graphs: Recreate native paper traces from 10.1101/2025.06.10.658191

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Recreate native paper traces — 10.1101/2025.06.10.658191

I can’t truthfully recreate the native (“paper trace”) graphs without access to the paper’s exact figure images or underlying numeric data (or at least the figure panels as images/PDF pages). Right now, I only have the DOI identifier you provided; I do not have the figure pixel data, axis scales, legends, or timepoints needed to digitize and match traces.

What I need from you (choose one)

Upload the paper PDF or the specific figure panel images containing the traces you want (preferred).
Or paste raw data tables if the paper provides them (supplementary CSV/Excel/text tables).
Or tell me the exact figure numbers + panel letters (e.g., “Figure 3B, 3C”) and upload only those panels as images.

Why I can’t “guess” the traces

“Recreating native paper traces” requires recovering (at minimum) pixel-to-data mapping for each axis (including log scales if present), and then digitizing each curve. Doing this without the figure source forces unverifiable assumptions about axis limits, scaling, and curve shape—so I won’t generate incorrect traces.

Once you upload the figure, I will do

Detect axis geometry (tick marks, labels, whether axes are linear/log) and infer the mapping from pixels to data units.
Digitize each curve to obtain a raw (x,y) series per trace.
Replot with Plotly to match the paper styling as closely as possible (line widths/colors where determinable from the panel).
Report raw digitized data (CSV embedded in the page) and provide a trace-vs-paper “sanity overlay” by re-rendering digitized points over the uploaded panel.

Ready-to-run: AI Scientist digitization agent

Click to run an iterative agent that will: extract panel axes, digitize curves, and generate Plotly trace reconstructions—using the figures you upload.

Quick clarification (answer in one line)

Which panel(s) do you mean by “native paper traces”? Please reply with: Figure # + panel letter(s) and what each x-axis represents.

Epistemic humility: If axis scaling is ambiguous (e.g., missing tick labels in cropped images), digitization confidence will be limited; I will flag uncertainties rather than fabricate exact values.