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<rss version="2.0"><channel><title>Calibrated Researcher field notes</title><link>https://calibratedresearcher.com/field-notes/</link><description>Practical field notes for PhD students and researchers on research methodology, writing papers, peer review and trustworthy AI, by Dr. Ilhame Ait Lbachir.</description><language>en</language><lastBuildDate>Wed, 14 Oct 2026 09:00:00 +0000</lastBuildDate><item><title>Uncertainty quantification explained for researchers</title><link>https://calibratedresearcher.com/field-notes/uncertainty-quantification-explained/</link><guid isPermaLink="true">https://calibratedresearcher.com/field-notes/uncertainty-quantification-explained/</guid><pubDate>Wed, 14 Oct 2026 09:00:00 +0000</pubDate><category>Trustworthy AI made clear</category><description>What uncertainty quantification means in deep learning, the main methods, how to test them, and what to report in a paper. With a free PDF kit.</description></item><item><title>Aleatoric vs epistemic uncertainty: what a model does not know, and why</title><link>https://calibratedresearcher.com/field-notes/aleatoric-vs-epistemic-uncertainty/</link><guid isPermaLink="true">https://calibratedresearcher.com/field-notes/aleatoric-vs-epistemic-uncertainty/</guid><pubDate>Wed, 14 Oct 2026 09:00:00 +0000</pubDate><category>Trustworthy AI made clear</category><description>Aleatoric uncertainty is noise in the data, epistemic uncertainty is what the model has not learned. Medical imaging examples and how to estimate each.</description></item><item><title>How to respond to reviewer comments: a point by point guide</title><link>https://calibratedresearcher.com/field-notes/how-to-respond-to-reviewer-comments/</link><guid isPermaLink="true">https://calibratedresearcher.com/field-notes/how-to-respond-to-reviewer-comments/</guid><pubDate>Wed, 14 Oct 2026 09:00:00 +0000</pubDate><category>Getting papers accepted</category><description>A calm, practical way to answer reviewer comments and write a rebuttal letter: sort the comments, respond point by point, and disagree with evidence.</description></item><item><title>Selective prediction: when a medical AI should say &quot;I am not sure&quot;</title><link>https://calibratedresearcher.com/field-notes/selective-prediction-in-medical-ai/</link><guid isPermaLink="true">https://calibratedresearcher.com/field-notes/selective-prediction-in-medical-ai/</guid><pubDate>Wed, 14 Oct 2026 09:00:00 +0000</pubDate><category>Trustworthy AI made clear</category><description>Selective prediction lets a model abstain on uncertain cases. How risk and coverage trade off, how to set a threshold honestly, and what to report in a paper.</description></item><item><title>Why a model&#x27;s confidence is often wrong: calibration and ECE explained</title><link>https://calibratedresearcher.com/field-notes/what-is-model-calibration/</link><guid isPermaLink="true">https://calibratedresearcher.com/field-notes/what-is-model-calibration/</guid><pubDate>Wed, 14 Oct 2026 09:00:00 +0000</pubDate><category>Trustworthy AI made clear</category><description>What model calibration means, how a reliability diagram and expected calibration error work, why modern neural networks are overconfident, and how to fix it.</description></item><item><title>AI can solve the problem. Can you still do the research?</title><link>https://calibratedresearcher.com/field-notes/using-ai-in-research-without-losing-your-skills/</link><guid isPermaLink="true">https://calibratedresearcher.com/field-notes/using-ai-in-research-without-losing-your-skills/</guid><pubDate>Mon, 05 Oct 2026 09:00:00 +0000</pubDate><category>Research in the age of AI</category><description>AI tools now solve many research problems faster than we can. What they still cannot do, two easy mistakes, and six habits to keep your skills growing.</description></item><item><title>A heatmap is not a confidence score: why medical AI needs explainability and uncertainty</title><link>https://calibratedresearcher.com/field-notes/explainable-ai-and-uncertainty-in-medical-imaging/</link><guid isPermaLink="true">https://calibratedresearcher.com/field-notes/explainable-ai-and-uncertainty-in-medical-imaging/</guid><pubDate>Tue, 29 Sep 2026 09:00:00 +0000</pubDate><category>Trustworthy AI made clear</category><description>Explainable AI shows where a model looked. Uncertainty shows how sure it is. Why medical imaging AI needs both, with a mammography screening example.</description></item><item><title>Your first year of a PhD: what it really is, and how to use it well</title><link>https://calibratedresearcher.com/field-notes/phd-first-year-guide/</link><guid isPermaLink="true">https://calibratedresearcher.com/field-notes/phd-first-year-guide/</guid><pubDate>Wed, 16 Sep 2026 09:00:00 +0000</pubDate><category>PhD basics</category><description>A practical guide to the first year of a PhD: what a doctorate trains you to do, how to work with your supervisor, and the habits that make later years easier.</description></item><item><title>How to choose a PhD research question that holds up to scrutiny</title><link>https://calibratedresearcher.com/field-notes/how-to-choose-a-phd-research-question/</link><guid isPermaLink="true">https://calibratedresearcher.com/field-notes/how-to-choose-a-phd-research-question/</guid><pubDate>Wed, 16 Sep 2026 09:00:00 +0000</pubDate><category>PhD basics</category><description>How to turn a vague PhD topic into a research question that is new, answerable, and defensible. Five tests, a four step method, and the red flags to avoid.</description></item><item><title>How to read a research paper efficiently: the three pass method for PhD students</title><link>https://calibratedresearcher.com/field-notes/how-to-read-a-research-paper/</link><guid isPermaLink="true">https://calibratedresearcher.com/field-notes/how-to-read-a-research-paper/</guid><pubDate>Wed, 16 Sep 2026 09:00:00 +0000</pubDate><category>PhD basics</category><description>Stop reading papers start to finish. The three pass method, a reviewer&#x27;s checklist for judging evidence, and a note template that turns reading into writing.</description></item></channel></rss>
