| Author here. I added fields so you can specify your first language (relevant link: https://en.wikipedia.org/wiki/Blue%E2%80%93green_distinction...) and colorblindness. FAQ: * I can't know your monitor's calibration, your ambient light, or your phone's brightness. Obviously, this will affect the results. However, I am tracking local time of day and device type, from which we should be able to infer whether night mode and default calibration has any aggregate effects. Anecdotally, thus far, I haven't found any effects of Android vs. iPhone (N=34,000). * The order is randomized. Where you start from can influence the outcome, but methodologically it's better to randomize so the aggregate results average over starting point. You can run the test several times to see how reliable this is for you. * It's common practice in psychophysics to use two alternatives rather than three (e.g. blue, green, something in the middle). It would be a fun extension, which you can handle with an ordered logistic regression. The code is open if you want to take a shot at it: https://github.com/patrickmineault/ismyblue * I will release aggregate results on my blog, https://neuroai.science * I am aware of most of the limitations of this test. I have run psychophysics experiments in a lab on calibrated CRTs during my PhD in visual neuroscience. *This is just entertainment*. I did this project to see if I could make a fun webapp in Vue.js using Claude Sonnet, and later cursor, given that I am not highly proficient in modern webdev. A secondary point was to engage people in vision science and get them to talk and think about perception and language. I think it worked! |