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          <h1 id="post-title">High-school Biology Practice Chapter Two</h1>

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<h1 id="methodology">Methodology</h1>
<p>Look at the exercise questions and list the variables of interest. Then, read the chapter to build a causal model with just those variables. Finally, without referring to the chapter, use your causal model to answer the questions. See what you missed and why and update your learning algorithm to catch it next time. Rinse and repeat till your causal model can answer each question with ease. When you’re satisfied, test your model against the Important Questions database.</p>
<p>Let’s focus on chapter two here.</p>
<h1 id="study-the-questions">Study the questions</h1>
<p>Key: What would cause the questions to be answered?</p>
<p>What are the variables of interest?</p>
<p>Once you’re interested in a variable, you need to find out its immediate causes and effects.</p>
<hr />
<p>time</p>
<p>classification system</p>
<p>economically important uses</p>
<p>types of bacteria</p>
<p>cell wall nature</p>
<p>algal bloom, and other such nonsense</p>
<p>viroids vs viruses</p>
<p>taxonomy - groups, etc. What do you forbid because of your knowledge of the taxonomy?</p>
<p>autotrophic, etc.</p>
<p>phycobiont, etc.</p>
<p>distinguish classes based on mode of nutrition, reproduction, etc.</p>
<p>characteristic features of different genuses?</p>
<p>structure, nature of genetic material</p>
<p>diseases</p>
<p>living or non-living</p>
<h1 id="lessons">Lessons</h1>
<p>One thing about the biology stuff I’ve read so far is that it’s all been static knowledge. “Plants are generally autotrophic”; “viruses don’t have cell walls”. It’s just been descriptive stuff.</p>
<p>There’s no talk about change over time or even over space. You don’t get to hear about how the system changes from one state to another. But that’s the main advantage of the locality of causality idea. You gain a terrific amount of information by leveraging proximity in time and space. No wonder I’m finding it hard to gain ground here.</p>
<p>Basically, I suspect that thinking in terms of causes is helpful when you want to <em>do</em> something - when you want to change the system to get certain effects - or you want to understand how the system will <em>change</em> over time and space. Apply force F to a mass m and you get acceleration F/m - that’s what I’m talking about: dynamic systems.</p>
<p>The stuff so far has been about background knowledge. It involved neither time nor space. It’s about the system as it is. Well, I don’t think that’s fully true. We have learned about modes of nutrition and reproduction, which tells you how you can starve or multiply some organisms.</p>
<p>But, in general, it’s been about “characteristics of bacteria” and “structure of viruses”. You tell me some diagnostic features of some organism, and I’ll tell you its entire life story. Well, isn’t that predictive power?</p>
<p>One limiting factor could be that we don’t have too many manipulation tools. Yes, at the advanced level, you have gene splicing and whatnot. You also have breeding and selection. But, apart from these costly tools, you have little else. It’s mostly about observation and making the best of what you’ve got.</p>
<p>Okay, assuming that causal models aren’t really useful here, how do we capture all this knowledge? More importantly, how do we compress it? Remember, our aim is to compress given knowledge as much as possible. Causal models have really shone at compressing in the past. Maybe it would help if we had actual causal knowledge. Right now, we just have observational data.</p>
<p>Ah! That’s the problem. It’s been non-interventional data so far. We’ve just seen correlations between organisms’ features. Maybe if we knew what caused panthers to be one way and tigers to be another way, we could store our information efficiently, instead of storing each characteristic redundantly. Basically, the thing that caused panthers to have different-colored skin from tigers probably also caused them to have night-vision (or whatever special powers they have).</p>
<p>I think background knowledge is just variables with no known causes. It’s stuff you just take for granted.</p>
<h1 id="compress">Compress</h1>
<p>How can we compress? In other words, what is redundant here? I think the taxonomical hierarchy aims to remove the redundancy. It captures the evolutionary ancestry.</p>
<p>Still, right now, it all seems so random. I’m unable to compress it. Bacteria do this and that. But why? What makes them have chlorophyll vs not?</p>
<p>They don’t even seem to make advance predictions. It’s not like they say if you have these characteristics, you will have those other ones too. That’s why I’m finding it hard. Why should some bacteria have tube shapes or whatever?</p>
<p>Actually, they are making advance predictions, narrow ones at that. They say that if you have the distinctive signs of a dog, then you will have all the other features of a dog. Else, their hypothesis is falsified. The predictions are all in the form of correlations, not causes. For one, you don’t get to know what will happen if you modify the organism. Next, you can’t predict the characteristics of a newly found species. You have to study them for yourself and see what features they exhibit. (Is this true? Won’t a new species that satisfies the requirements for “big cat” be similar in other ways to lions and tigers?)</p>
<p>Another perspective: what kind of questions can they ask when all you have are correlations? Can they ask causal questions? Is it all just about recall from memory or is there some computation you have to do?</p>
<h1 id="aim">Aim</h1>
<p>My aim is to get predictive power and compress the model as much as possible.</p>
<h1 id="types-of-questions">Types of Questions</h1>
<p>In short, there seem to be two types of questions: descriptive questions (describe meiosis; distinguish cytokinesis from karyokinesis), and causal or counterfactual questions (can there be DNA replication without cell division?).</p>
<p>Further causal questions include “factors affecting the rate of diffusion”, “what role do porins play in diffusion?”, “what are the factors affecting water potential”, etc.</p>
<p>For the descriptive questions, just aim to get their anticipation-constraints instead of causal structures. It would probably be in the form of correlations. This way I can ask for their narrow predictions for important variables. Basically, take each concept - species, eukaryotes, etc. - and hold up different variables to it and ask what it predicts.</p>
<p>Be careful to talk about only the immediate causes and immediate effects. Don’t say what the liver does throughout digestion; just talk about its immediate output (bile). For each part of the digestive system, consider just its immediate input and output. The anus doesn’t care about what happened four hours ago at the start of digestion. If the rectum holds faeces and a few other conditions are satisfied, it will excrete the waste. That is all.</p>

<div class="info">Created: November  7, 2015</div>
<div class="info">Last modified: September 28, 2019</div>
<div class="info">Status: in-progress</div>
<div class="info"><b>Tags</b>: biology practice</div>

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