Help yourself learn/memorize 50 terms from Krebs Cycle

Krebs Cycle Mastery (SM2 Algorithm)

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Excellent work. All pending components have been optimized via the SM-2 engine. Check back tomorrow for your next scheduled interval review.

Some important features of this post are:

• The SM-2 Spaced Repetition Engine: No more useless cramming. The built-in SuperMemo-2 algorithm tracks your memory strength and schedules your reviews at the exact mathematical moment you’re about to forget.
• 50 High-Yield Cloze Flashcards: Interactive, fill-in-the-blank prompts covering everything from irreversible checkpoints and cofactors (like TPP and biotin) to metabolic poisons (fluoroacetate and arsenite).
• 6-Tier Precision Grading: Rate your recall from 0 (Blank) to 5 (Perfect) to dynamically customize your learning curve.
• Seamless Progress Tracking: Features a built-in progress bar and automated local storage, meaning it saves your exact algorithmic memory weights so you can pick right up tomorrow.

N.B.: Kindly inform in case of any errors or mistakes in this post.

Bayes' Theorem - Educational Content

Bayes' Theorem Visualizer

Understand how to revise predictions based on new data.

The Definition

Bayes' Theorem is a fundamental formula in probability that calculates the updated probability of an event (A) given new evidence (B). It relates the likelihood of the evidence to the prior belief.

P(A|B) =

P(B|A) ⋅ P(A) P(B)

Where:
P(A|B) The updated probability after seeing the evidence. Also called the result. is the Posterior,
P(B|A) The probability of seeing this evidence IF the hypothesis is true. is the Likelihood,
P(A) Your initial belief before seeing any new evidence. is the Prior, and
P(B) The total probability of the evidence occurring, regardless of whether the hypothesis is true or false. is the Evidence.

 Interactive Practice

Memorize the Formula

Try writing the theorem below to commit it to memory.

P(A|B) = [P(B|A) * P(A)] / P(B)

Bayesian Probability Interactive

Adjust sliders to see how evidence updates belief.

TP

FP

Final Probability P(H|E)

16.7%

Given a positive result, this is the chance it's actually true.

P(H) Prior 1% The "Prior" width: How common is the condition?

P(E|H) Sensitivity 99% The height of the Dark Blue box.

P(E|¬H) False Pos 5% The height of the Red box.

Memorize over 170 chemical structures by practically drawing and using Spaced Repetition algorithm

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Chemical Structures SRS

Draw the structure, then rate your memory!

Choose a subject: All Subjects General Chemistry Organic Chemistry Biochemistry Common Drugs & Molecules A Level Chemistry O Level Chemistry Medicinal Chemistry Inorganic Chemistry Physical Chemistry Analytical Chemistry Olympiad Chemistry (IChO / IJSO) GRE Chemistry & University Level Advanced Chemistry (IUPAC / Professional)

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N5 JLPT - Practice writing Japanese Characters - Five at a time - Part 9

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N5 JLPT - Practice writing Japanese Characters - Five at a time - Part 8

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Aakifah telling the meanings of Ta'awwudh and Tasmiyah (Urdu)

In this video (in Urdu), Aakifah Usman Paracha tells the meanings of Ta'awwudh and Tasmiyah. Hope, it will help our children in learning their meanings.

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