The Metaculus Journal

Metaculus Inc.

Audio readings from The Metaculus Journal The Metaculus Journal publishes essays on topics in science, mathematics, technology, policy, and politics—all fortified by testable predictions. read less

The Path to Controlling Cancer
Sep 4 2022
The Path to Controlling Cancer Treating cancer is a battle against exponential growth of mutating cells, so even breakthrough drugs may offer only incremental increases in survival time before residual tumors rebound. But as we learn more about the fundamental mechanisms of cancer, we can target those processes more directly. When will people diagnosed with the most lethal cancers more often than not survive for years? I will examine progress in cancer treatment and speculate on the path toward managing intractable cancer types. Cancer’s complexity Why are several-year survival rates the currency of progress in fighting cancer? It is easy to wonder, especially if you have a personal connection to cancer, why we keep seeing breakthroughs that result in a small bump in survival times rather than cures. In short, cancer cells are human cells and they evolve. It is easy to kill cancer cells, but difficult to kill them without destroying the patient’s body. And it is extremely difficult to kill every one of them before they evolve again. Most mutations either have no effect or they kill the cell and therefore self-correct. Even when mutations self-perpetuate against all odds, the body has many defenses against them. The chances of a combination of mutations evading all this is vanishingly small, but there are trillions of opportunities for it to happen in the body. By the time it is diagnosed, a tumor has already bested a solid wall of defenses. That means there is no easy fix for cancer, and a variety of treatments are used—primarily different types of surgery, radiotherapy, and chemotherapy. The relative importance of each of these will continue to evolve. Predicting survival rates
Biosecurity Vulnerabilities of American Food Supply
Jun 14 2022
Biosecurity Vulnerabilities of American Food Supply In the early summer of 1968, farmers in Louisiana noticed small, elongated brown lesions running down green leaves of corn. These plants quickly died or experienced extensive rot that rendered the vegetable inedible. By 1970, these symptoms could be seen on acre after acre of corn from Florida to North Dakota. The disease soon had a name: southern corn leaf blight (SCLB). The fungal pathogen that caused SCLB, although virulent, could only infect a specific hybrid of corn. This hybrid, which was bred to develop a more efficient ear, was one of the most planted seeds in the country at the time. Once the cause of the vulnerability was discovered, seed companies simply switched hybrids. By 1972, the American corn market rebounded—although not before suffering major economic losses. The world is now more cognizant of catastrophic biological risk. However, the focus is mainly on direct impacts to human health. The 1970 SCLB epidemic (technically termed epiphytotic) is a prime example of a fast moving plant disease that can inflict sudden and outsized damage to the agricultural industry. Is there significant biorisk to America’s food production and supply? In light of increasing food demand for a growing population and the easy conveyance of biological threats via global trade/travel, let’s explore potential biosecurity vulnerabilities in America’s agricultural industry and discuss possible solutions to mitigate these vulnerabilities.
Renewables Forecasting
May 16 2022
Renewables Forecasting Published by RyanBeck on Feb 14, 2022. In a recent article about solar power, Tom Chivers described how growth in solar power has outpaced many forecasts, as well as the challenges involved in accurately forecasting trends in solar power. Making accurate forecasts about the future of solar is important for understanding what future CO₂ emissions may look like and what our chances of mitigating the effects of climate change are. In this essay I attempt to estimate the bounds of solar and wind growth. Pieces of the puzzle The first stage of putting together an energy forecast is to understand the relevant background information. What the different units mean, how different energy types can be compared directly, and what the previous trends look like are all essential if we want to understand the future of electricity generation. Power and energy When electricity generation is talked about it can be easy to confuse power and energy. Power is a measure of the rate at which work is being done. Power is commonly measured in watts when discussing electricity generation. Energy is how much work has been done, or the amount of power exerted over time. It is commonly measured in watt-hours, as it is the amount of power (watts) multiplied by the amount of time that power was exerted (hours). We can imagine power as the rate of water flowing out of a hose, while energy is the amount of water in the bucket that the hose is filling after a given period of time. These are important concepts when talking about electricity generation. When a new power plant is installed it’s usually described in terms of either its power or its capacity. But discussions about what a power plant produces are in terms of energy–such as descriptions of how much energy the plant generated in a given year.
Action Ontologies, Computer Ontologies
May 9 2022
Action Ontologies, Computer Ontologies The following essay is by Jacob Falkovich who writes at The mystery of perception Out in the universe, there are merely atoms¹ and the void. On the table in front of you, there’s a ripe tomato. Inside your skull is a brain, a collection of neurons that have no direct access to either atoms or tomatoes — only the electrochemical state of some other neurons. And yet your brain is able to perceive a tomato and various qualities of it: red, round, three-dimensional, real. On the common how-it-seems view of perception, there is no particular mystery to this. In this view, light from the tomato hits your eyes and is decoded “bottom-up” in your brain into simple features such as color, shape, and size, which are then combined into complex perceptions such as “tomato.” This view is intuitively appealing: Whenever we perceive a tomato we find the actual tomato there; thus we believe the tomato to be the sole and sufficient cause of the perception. A closer look begins to challenge this intuition. You may see a tomato up close or far away, at different angles, partially obscured, in dim light, etc. The perception of it as being red, round, and a few inches across doesn’t change even though the light hitting your retina is completely different in each case: different angles of your visual field, different wavelengths, etc.  Take color for example. Naively, the perception of color is the detection of wavelengths of light, and yet you perceive the same color from green light (530 nm) as you do from a mix of blue (470 nm) and yellow (570 nm). A white piece of paper will appear white in your perception even though it actually reflects the wavelengths of the light around it: blue under a clear sky, green if held close to grass, orange by candle light. The strawberries in the image below appear red even though there isn’t a single red-hued pixel in it. Wherever the perception of color is coming from, it is certainly not the mere bottom-up decoding of light wavelengths.