refactor: extract 6 prediction signals into Signal classes

The 803-line NationalFuelPredictionService had six private compute*Signal
methods, a private linearRegression helper, and a private disabledSignal
shape factory all crammed together. Each signal is now an independently
testable class.

- App\Services\Prediction\Signals\Signal — interface
- App\Services\Prediction\Signals\SignalContext — input value object
  (FuelType + optional lat/lng + hasCoordinates() helper)
- App\Services\Prediction\Signals\AbstractSignal — shared
  disabledSignal() and linearRegression() helpers
- TrendSignal, DayOfWeekSignal, BrandBehaviourSignal, StickinessSignal,
  RegionalMomentumSignal, OilSignal — one class each, extending
  AbstractSignal

NationalFuelPredictionService receives the 6 signal classes via constructor
injection and orchestrates them. The lat/lng null-guard for regional
momentum now lives inside RegionalMomentumSignal::compute() so the
coordinator no longer branches on coordinate presence.

Aggregation, weekly summary, and reasoning helpers stay in the service
for now — they are coupled to the public predict() output shape and are
candidates for a follow-up extraction once a stable API is locked in.

Service: 803 → 414 lines.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

app/Services/Prediction/Signals/StickinessSignal.php

@@ -0,0 +1,53 @@
+<?php
+
+namespace App\Services\Prediction\Signals;
+
+use Illuminate\Support\Facades\DB;
+
+final class StickinessSignal extends AbstractSignal
+{
+    public function compute(SignalContext $context): array
+    {
+        $isSqlite = DB::connection()->getDriverName() === 'sqlite';
+        $diffExpr = $isSqlite
+            ? 'CAST((julianday(MAX(price_effective_at)) - julianday(MIN(price_effective_at))) AS INTEGER)'
+            : 'DATEDIFF(MAX(price_effective_at), MIN(price_effective_at))';
+
+        $rows = DB::table('station_prices')
+            ->where('fuel_type', $context->fuelType->value)
+            ->where('price_effective_at', '>=', now()->subDays(30))
+            ->selectRaw("station_id, COUNT(*) as changes, {$diffExpr} as span_days")
+            ->groupBy('station_id')
+            ->having('changes', '>', 1)
+            ->having('span_days', '>', 0)
+            ->get();
+
+        if ($rows->count() < 10) {
+            return $this->disabledSignal('Insufficient stickiness data (need 10+ stations with price history)');
+        }
+
+        $avgHoldDays = $rows->avg(fn ($r) => $r->span_days / ($r->changes - 1));
+        $avgHoldDays = round((float) $avgHoldDays, 1);
+
+        $score = match (true) {
+            $avgHoldDays < 2 => -0.1,
+            $avgHoldDays > 5 => 0.1,
+            default => 0.0,
+        };
+
+        $detail = match (true) {
+            $avgHoldDays < 2 => "Volatile prices (avg hold: {$avgHoldDays} days) — harder to predict.",
+            $avgHoldDays > 5 => "Sticky prices (avg hold: {$avgHoldDays} days) — more predictable.",
+            default => "Normal hold period (avg: {$avgHoldDays} days).",
+        };
+
+        return [
+            'score' => $score,
+            'confidence' => min(1.0, $rows->count() / 200),
+            'direction' => 'stable',
+            'detail' => $detail,
+            'data_points' => $rows->count(),
+            'enabled' => true,
+        ];
+    }
+}