bao han

Part of the RigorMed team. I write about reproducible research workflows, evidence checks, and MCP. RigorMed helps researchers turn papers, data and drafts into outputs their teams can review.

Joined on Nov 2, 2026 https://rigormed.com/en

bao han

Nov 13

Check for source overlap before you trust an ML test score

#data #datascience #machinelearning #python

2 min read

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bao han

Nov 12

Compare figure panel IDs with the manuscript legend

#automation #python #testing

1 min read

bao han

Nov 12

Check for editable text in a reconstructed PowerPoint slide

#programming #python #tutorial

2 min read

bao han

Nov 11

Check that a research CSV join preserves one row per participant

#research

1 min read

bao han

Nov 11

Catch unexpected missing-value codes in a research CSV

#python

1 min read

bao han

Nov 10

Keep unknown registry outcomes separate from observed negatives in Python

#research

1 min read

bao han

Nov 10

Catch repeated patient-visit keys before joining two research exports

#python #data

1 min read

bao han

Nov 9

Catch a lost time window in an abstract editing pipeline

#dataquality

1 min read

bao han

Nov 9

Carry the analysis denominator into an edited abstract

#data #softwaredevelopment #softwareengineering

2 min read

bao han

Nov 8

Preserve a missing count when drafting an abstract results table

#data #programming #python #softwaredevelopment

1 min read

bao han

Nov 7

Flag a changed comparison operator in an edited abstract

#code #coding #programming #python

2 min read

bao han

Nov 7

Keep reviewer anchors tied to one manuscript revision

#automation #coding #python

2 min read

bao han

Nov 6

Keep decimal values intact when preparing manuscript review units

#python

3 min read

bao han

Nov 6

Bind an abstract edit to the current source before comparing wording

#ai #python

3 min read

bao han

Nov 5

A unit audit beside an abstract edit: use Decimal, then review the sentence

#research #python

3 min read

bao han

Nov 5

Keep the “not” when handing off a research reading note

#python

3 min read

bao han

Nov 5

Compute the comparison without inventing the study

#python

3 min read

bao han

Nov 4

Group reference candidates without deleting the evidence trail

#python

3 min read

bao han

Nov 4

A complete claim matrix is not verified evidence: keep both results in Python

#code #programming #python #science

4 min read

bao han

Nov 4

Check a CSV's missing-data contract before drawing a line

#python

4 min read

bao han

Nov 3

Keep missing days missing: a Python evidence table for paper dates

#python

4 min read

bao han

Nov 3

Unique rows are not an unseen-subject test: audit the splitting unit

#machinelearning

4 min read

bao han

Nov 3

A paper-to-tool interface needs a scientific output contract

#machinelearning

4 min read

bao han

Nov 3

A 95% accurate research classifier can miss every useful candidate

#python

4 min read

DEV Community

bao han

Badges

Writing Debut

Check for source overlap before you trust an ML test score

Want to connect with bao han?

Compare figure panel IDs with the manuscript legend

Check for editable text in a reconstructed PowerPoint slide

Check that a research CSV join preserves one row per participant

Catch unexpected missing-value codes in a research CSV

Keep unknown registry outcomes separate from observed negatives in Python

Catch repeated patient-visit keys before joining two research exports

Catch a lost time window in an abstract editing pipeline

Carry the analysis denominator into an edited abstract

Preserve a missing count when drafting an abstract results table

Flag a changed comparison operator in an edited abstract

Keep reviewer anchors tied to one manuscript revision

Keep decimal values intact when preparing manuscript review units

Bind an abstract edit to the current source before comparing wording

A unit audit beside an abstract edit: use Decimal, then review the sentence

Keep the “not” when handing off a research reading note

Compute the comparison without inventing the study

Group reference candidates without deleting the evidence trail

A complete claim matrix is not verified evidence: keep both results in Python

Check a CSV's missing-data contract before drawing a line

Keep missing days missing: a Python evidence table for paper dates

Unique rows are not an unseen-subject test: audit the splitting unit

A paper-to-tool interface needs a scientific output contract

A 95% accurate research classifier can miss every useful candidate