Cathode-ray tubeA cathode-ray tube (CRT) is a vacuum tube containing one or more electron guns, which emit electron beams that are manipulated to display images on a phosphorescent screen. The images may represent electrical waveforms (oscilloscope), pictures (television set, computer monitor), radar targets, or other phenomena. A CRT on a television set is commonly called a picture tube. CRTs have also been used as memory devices, in which case the screen is not intended to be visible to an observer.
Confirmation biasConfirmation bias is the tendency to search for, interpret, favor, and recall information in a way that confirms or supports one's prior beliefs or values. People display this bias when they select information that supports their views, ignoring contrary information, or when they interpret ambiguous evidence as supporting their existing attitudes. The effect is strongest for desired outcomes, for emotionally charged issues, and for deeply entrenched beliefs.
Systemic biasSystemic bias is the inherent tendency of a process to support particular outcomes. The term generally refers to human systems such as institutions. Systemic bias is related to and overlaps conceptually with institutional bias and structural bias, and the terms are often used interchangeably. According to Oxford Reference, institutional bias is "a tendency for the procedures and practices of particular institutions to operate in ways which result in certain social groups being advantaged or favoured and others being disadvantaged or devalued.
Cognitive biasA cognitive bias is a systematic pattern of deviation from norm or rationality in judgment. Individuals create their own "subjective reality" from their perception of the input. An individual's construction of reality, not the objective input, may dictate their behavior in the world. Thus, cognitive biases may sometimes lead to perceptual distortion, inaccurate judgment, illogical interpretation, and irrationality. While cognitive biases may initially appear to be negative, some are adaptive.
Hot cathodeIn vacuum tubes and gas-filled tubes, a hot cathode or thermionic cathode is a cathode electrode which is heated to make it emit electrons due to thermionic emission. This is in contrast to a cold cathode, which does not have a heating element. The heating element is usually an electrical filament heated by a separate electric current passing through it. Hot cathodes typically achieve much higher power density than cold cathodes, emitting significantly more electrons from the same surface area.
Hindsight biasHindsight bias, also known as the knew-it-all-along phenomenon or creeping determinism, is the common tendency for people to perceive past events as having been more predictable than they were. People often believe that after an event has occurred, they would have predicted or perhaps even would have known with a high degree of certainty what the outcome of the event would have been before the event occurred.
Transmission electron microscopyTransmission electron microscopy (TEM) is a microscopy technique in which a beam of electrons is transmitted through a specimen to form an image. The specimen is most often an ultrathin section less than 100 nm thick or a suspension on a grid. An image is formed from the interaction of the electrons with the sample as the beam is transmitted through the specimen. The image is then magnified and focused onto an imaging device, such as a fluorescent screen, a layer of photographic film, or a sensor such as a scintillator attached to a charge-coupled device.
Bias–variance tradeoffIn statistics and machine learning, the bias–variance tradeoff is the property of a model that the variance of the parameter estimated across samples can be reduced by increasing the bias in the estimated parameters. The bias–variance dilemma or bias–variance problem is the conflict in trying to simultaneously minimize these two sources of error that prevent supervised learning algorithms from generalizing beyond their training set: The bias error is an error from erroneous assumptions in the learning algorithm.
