Model Scorecard: What Counts as an Explanation?

A model is not just an answer that feels satisfying. A model earns trust by making predictions, surviving checks, and explaining many observations with the same rules. 
 The Scorecard 
 Criterion Strong model Weak model Prediction States what should happen before looking. Explains only after the result is known. Precision Uses numbers, locations, dates, and tolerances. Uses vague words like “perspective,” “energy,” or “deception” without calculation. Scope Explains related evidence with the same geometry. Needs a different exception for every topic. Risk Could be proven wrong by a clear observation. Cannot name any possible falsifier. Independence Can be checked by ordinary observers and independent sources. Depends on dismissing every conflicting observer as fooled or corrupt. 
 Apply It to Flat-Earth Claims 
 When someone offers a flat-earth explanation, score it. Does it predict sunrise direction, route distances, southern stars, eclipse timing, tides, and horizon behavior together? Or does it only answer the one meme currently on screen? 
 One Useful Question 
 What would this model predict if we changed the location, date, or direction? A real model can travel. A fragile claim only works in its original meme.