refactor!: the joint is reached through Joint, not mirrored on History

`posterior_of`, `posterior_of_at` and `expected_variance_reduction`
existed twice: once on `Joint`, and once on `History` as one-shot
wrappers whose whole body was `self.joint()?.<same>(..)`.

The wrappers re-factorised on every call — their own docs said so,
warning the reader to take a `Joint` instead — and they were what
smuggled the scored-only precondition onto the flat surface. A user
following the quickstart builds a ranked history, sees `posterior_of` in
the method list, and it never works. `h.joint()?.posterior_of(..)` is
one call longer and tells the truth: you need a joint, and a joint needs
a scored history.

That leaves three tiers instead of a flat surface with a hidden
precondition: `History` fits and reads, `predict_*` forecasts, `Joint`
answers exact joint questions.

`predict_margin` was itself calling `self.posterior_of`; it goes through
`self.joint()?` directly now.

The `Joint` methods' docs referred back to the wrappers for their real
content ("Identical to `History::posterior_of`, without re-paying the
factorisation"), so they now carry it: what a linear functional means,
which appearance each competitor is read at, and why
`expected_variance_reduction` belongs on the handle.

`tests/joint_handle.rs` had three tests comparing the wrapper against
the handle. That comparison is gone, but the property behind it is not —
they now compare a *reused* joint against a *fresh* one per question,
which is the actual correctness claim behind caching the factorisation
(#51), without the wrapper in the middle.

Closes #78.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_011hcFjNDmHXZF8URGLku5zZ

tests/cross_process_determinism.rs

@@ -84,13 +84,17 @@ fn fingerprint() -> String {
     let known = "p0".to_string();
     terms.push((&known, -1.0));
 
-    let posterior = h.posterior_of(&terms).unwrap();
+    let posterior = h.joint().unwrap().posterior_of(&terms).unwrap();
 
     let a = "p0".to_string();
     let b = "p1".to_string();
     let target = [(&a, 1.0), (&b, -1.0)];
     let teams: [&[&String]; 2] = [&[&a], &[&b]];
-    let evr = h.expected_variance_reduction(&teams, &target).unwrap();
+    let evr = h
+        .joint()
+        .unwrap()
+        .expected_variance_reduction(&teams, &target)
+        .unwrap();
 
     let curves = h.learning_curves();
     let mut curve_bits: u64 = 0;