Add Composite Score layer with adjustable weights

[Kovbo]

Summary

• Adds a fifth visualization layer — Composite Score — that combines all four existing metrics (pay, outlook, education, AI exposure) into a single color-coded view
• Each factor's importance is controlled by interactive sliders (0–10), so users can personalize the view: someone prioritizing income cranks up Pay, someone worried about automation cranks up AI Exposure, etc.
• Green tiles = high-opportunity jobs (well-paying, growing, accessible, AI-resilient); red tiles = low-opportunity

Motivation

The existing four layers each show a single dimension, but people evaluating career options care about multiple factors simultaneously. A nurse might score well on outlook but poorly on pay; a software developer scores high on pay but high on AI exposure. There was no way to see the combined picture or weight the factors by personal priorities.

This layer lets users answer questions like "What jobs pay well, are growing, don't require a PhD, and aren't threatened by AI?" — and adjust the definition of "well" for each axis.

Details

• Composite score = weighted average of four normalized components:
  • Pay: log-scaled $50K–$250K (jobs under $50K score 0)
  • Outlook: BLS projected growth, normalized -12% to +12%
  • Education: lower requirement = higher score
  • AI Exposure: lower exposure = higher score
• Sliders default to 10 (equal weight); setting any slider to 0 removes that factor entirely
• Stats panel shows: weighted average, tier breakdown, cross-tabs by pay and education, and excellent-tier job count
• Tooltip shows the composite percentage with a progress bar