Is your model really ‘comprehensive’?

I’ve noticed again and more papers using the denominate “comprehensive model”. This phrase grates each time, and this post is almost why.

I thought this might true be me getting old and surly, so I plotted the mentions of the phrases “of extensive application mathematical model” or “comprehensive model” in ‘Topic’ in Web of Science excessively the years in Figure 1. Sure enough, more papers in recent years feature models that are comprehensive*.

Figure 1: The Rise of Comprehensive Models!

Figure 1: the ascend of Comprehensive Models! Mentions of “Comprehensive Models” or “Comprehensive Mathematical Models” in Web of Science 1945 – 2015.

So for what cause don’t I think a strict model is ever comprehensive?

Usually by comprehensive the authors mean something like this describes principally of what we’ve seen well sufficiency to say/predict something (or in like manner to within the observational error bounds in more physics experiments). Perhaps their model integrates knowledge/theories that weren’t part of a unmixed conceptual framework/mathematical model before. That’s cyclopean – but it isn’t of great scope!

This post is really an absolve to plug and discuss the following quotation from James Black (physiologist and Nobel Prize winner in opposition to developing the first beta-blockers). He summarises the sort of mathematical models are and aren’t, and the kind of they are for, beautifully:

[Mathematical] models in analytical pharmacology are not meant to have existence descriptions, pathetic descriptions, of nature; they are designed to be accurate descriptions of our pathetic thinking about nature. They are meant to show up assumptions, define expectations and help us to project new tests.

Sir James Black (1924 – 2010)
Nobel Prize Lecture, 1988**

A precise model isn’t supposed to subsist a comprehensive representation of a combination of parts to form a whole – it’s always going to subsist a pathetic representation in many ways! Models constitute simplifying assumptions (by definition***), generally ignoring things that we have an opinion will make a smaller difference to the model’s predictions than the things that we have included (usually things that happen really fast/slow or that are in reality small/big).

What models do give permission to us to do is see exactly what we would expect to happen grant that the system works in the straightforward(ish!) way we think it does. Then that have power to teach us loads about whether the body does work as we thought it did, or whether matter fundamental is missing from our apprehension.

We’ll always be able to reach back and add more detail during the time that time goes on, we learn besides, and can measure more things. So that ways and ~ that a model is never proficient, and never comprehensive. So I’d tell let’s avoid using the expression. comprehensive to describe any kind of prototype!

A Large Confession: I thought the vocable comprehensive implied ‘includes everything’. Purely to back up my position I looked it up, and trustworthy enough one of the OED’s definitions is “grasps or understands (a body) fully” which a model never does; on the other hand another is “having the note of comprising or including much; of capacious content or scope” which might be OK! Hmmmm… given the ambiguity I still conclude we’d wagerer avoid the word anyway! But I’ll obstacle you make your own minds up:

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* Yeah, I be assured of I really need to divide by the total number of papers that cursory reference models etc. but that’s harder to inquiry sensibly – and WoS doesn’t summarise data for over 10,000 papers!

** You be possible to watch his Nobel Prize lecture online. He’s very a remarkable man and invented/discovered lots of classes of completely of recent origin drugs, interestingly – as you can see in the video – he used modelling a hap. His modelling would now be component of the trendy new field of Quantitative Systems Pharmacology (although I’d say we’ve been doing it in favor of years

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