Implement 10 platform features: evaluation UX, admin tools, AI summaries, applicant portal

Batch 1 - Quick Wins:
- F1: Evaluation progress indicator with touch tracking in sticky status bar
- F2: Export filtering results as CSV with dynamic AI column flattening
- F3: Observer access to analytics dashboards (8 procedures changed to observerProcedure)

Batch 2 - Jury Experience:
- F4: Countdown timer component with urgency colors + email reminder service with cron endpoint
- F5: Conflict of interest declaration system (dialog, admin management, review workflow)

Batch 3 - Admin & AI Enhancements:
- F6: Bulk status update UI with selection checkboxes, floating toolbar, status history recording
- F7: AI-powered evaluation summary with anonymized data, OpenAI integration, scoring patterns
- F8: Smart assignment improvements (geo diversity penalty, round familiarity bonus, COI blocking)

Batch 4 - Form Flexibility & Applicant Portal:
- F9: Evaluation form flexibility (text, boolean, section_header types, conditional visibility)
- F10: Applicant portal (status timeline, per-round documents, mentor messaging)

Schema: 5 new models (ReminderLog, ConflictOfInterest, EvaluationSummary, ProjectStatusHistory, MentorMessage), ProjectFile extended with roundId + isLate.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

src/server/routers/export.ts

@@ -228,6 +228,103 @@ export const exportRouter = router({
       }
     }),
 
+  /**
+   * Export filtering results as CSV data
+   */
+  filteringResults: adminProcedure
+    .input(z.object({ roundId: z.string() }))
+    .query(async ({ ctx, input }) => {
+      const results = await ctx.prisma.filteringResult.findMany({
+        where: { roundId: input.roundId },
+        include: {
+          project: {
+            select: {
+              title: true,
+              teamName: true,
+              competitionCategory: true,
+              country: true,
+              oceanIssue: true,
+              tags: true,
+            },
+          },
+        },
+        orderBy: { project: { title: 'asc' } },
+      })
+
+      // Collect all unique AI screening keys across all results
+      const aiKeys = new Set<string>()
+      results.forEach((r) => {
+        if (r.aiScreeningJson && typeof r.aiScreeningJson === 'object') {
+          const screening = r.aiScreeningJson as Record<string, Record<string, unknown>>
+          for (const ruleResult of Object.values(screening)) {
+            if (ruleResult && typeof ruleResult === 'object') {
+              Object.keys(ruleResult).forEach((k) => aiKeys.add(k))
+            }
+          }
+        }
+      })
+
+      const sortedAiKeys = Array.from(aiKeys).sort()
+
+      const data = results.map((r) => {
+        // Flatten AI screening - take first rule result's values
+        const aiFlat: Record<string, unknown> = {}
+        if (r.aiScreeningJson && typeof r.aiScreeningJson === 'object') {
+          const screening = r.aiScreeningJson as Record<string, Record<string, unknown>>
+          const firstEntry = Object.values(screening)[0]
+          if (firstEntry && typeof firstEntry === 'object') {
+            for (const key of sortedAiKeys) {
+              const val = firstEntry[key]
+              aiFlat[`ai_${key}`] = val !== undefined ? String(val) : ''
+            }
+          }
+        }
+
+        return {
+          projectTitle: r.project.title,
+          teamName: r.project.teamName ?? '',
+          category: r.project.competitionCategory ?? '',
+          country: r.project.country ?? '',
+          oceanIssue: r.project.oceanIssue ?? '',
+          tags: r.project.tags.join(', '),
+          outcome: r.outcome,
+          finalOutcome: r.finalOutcome ?? '',
+          overrideReason: r.overrideReason ?? '',
+          ...aiFlat,
+        }
+      })
+
+      // Build columns list
+      const baseColumns = [
+        'projectTitle',
+        'teamName',
+        'category',
+        'country',
+        'oceanIssue',
+        'tags',
+        'outcome',
+        'finalOutcome',
+        'overrideReason',
+      ]
+      const aiColumns = sortedAiKeys.map((k) => `ai_${k}`)
+
+      // Audit log
+      await logAudit({
+        prisma: ctx.prisma,
+        userId: ctx.user.id,
+        action: 'EXPORT',
+        entityType: 'FilteringResult',
+        detailsJson: { roundId: input.roundId, count: data.length },
+        ipAddress: ctx.ip,
+        userAgent: ctx.userAgent,
+      })
+
+      return {
+        data,
+        columns: [...baseColumns, ...aiColumns],
+      }
+    }),
+
   /**
    * Export audit logs as CSV data
    */