engine: tune the default world to a soft program

DefaultConfig now describes a more realistic world: a moderately novel fake
(novelty 0.3), some ambient harm awareness (0.2), and a strong but imperfect
education program (programEffect 0.8) so educated students mostly, not always,
refuse. The headline shifts from 99/70/7 (a perfect program) to 100/83/21 out
of 120 (83/69/18 percent): no program >> random >> most-connected still holds,
targeting still wins by ~4x, but the program is no longer a perfect wall.
Golden values re-pinned in the engine and API tests; the preset base matches.
The forward-chance formula test now neutralises its baseline so it pins the
formula, not the tuned defaults.

web/src/presets/deepfake-school.ts

@@ -28,9 +28,9 @@ export const deepfakeSchoolPreset: StudyPreset = {
     edgesPerNode: 3,
     triangleProb: 0.45,
     forwardProb: 0.38,
-    novelty: 0,
-    harmAwareness: 0,
-    programEffect: 1,
+    novelty: 0.3,
+    harmAwareness: 0.2,
+    programEffect: 0.8,
     numEducated: 36,
     origin: 0,
     graphSeed: 17,