fix(about): per-table count fallback so missing tables don't blank everything

The whole-block try/rescue around fetch_stats meant any single failing
query (a missing dev table, a transient pg blip) zeroed all 10
counters. Each count_exact/1 + count_estimate/1 now uses Repo.query/2
and falls back to 0 only for its own column. Bumps the inline 9-factor
prose to 10-factor and pulls the contacts headline from the live count
instead of a stale '58k+' string.

Adds a CLAUDE.md note prompting future updates to refresh /about's
prose when factor counts, data sources, or schema scale change.

CLAUDE.md

@@ -221,6 +221,10 @@ User submits QSO → enqueue_for_qso() → weather/hrrr/terrain/iemre workers
 - **Always run `cargo clippy --all-targets -- -D warnings` before committing Rust changes.** The Forgejo CI step runs clippy with warnings-as-errors and a passing local `cargo build` does NOT catch lints (e.g. `manual_range_contains`, `iter_kv_map`, `useless_format`). A clippy failure blocks the image build and the deploy. The Rust precommit recipe is in the `Commands` section.
 - The CI build pipeline runs `cargo clippy --all-targets -- -D warnings && cargo test --release && cargo build --release`. Match this locally — `cargo build` alone is not enough.
 
+### `/about` page maintenance
+- Refresh `lib/microwaveprop_web/live/about_live.ex` whenever **algorithm structure**, **factor count or weights**, **major data sources**, **schema scale claims (e.g. "58k+ contacts")**, or **roadmap items** change. The dashboard counts auto-refresh from the DB; the prose blocks (overview, "How it works", "How it's built", "What's next") do not.
+- The page renders a per-table count via `count_exact/1` and `count_estimate/1`. Each query is wrapped individually so a missing dev table doesn't blank the whole dashboard — keep that pattern when adding new stats.
+
 ### Deployment
 - Production runs on Kubernetes (`home-cluster` context, `prop` namespace) — use `kubectl -n prop ...`
 - Deployment name `prop` (3 replicas). Inspect with `kubectl -n prop get pods`, `kubectl -n prop logs deploy/prop`, `kubectl -n prop exec deploy/prop -- ...`

lib/microwaveprop_web/live/about_live.ex

@@ -76,27 +76,29 @@ defmodule MicrowavepropWeb.AboutLive do
               profiles. We derive refractivity profiles, minimum refractivity
               gradient, ducting detection, boundary-layer depth, and precipitable
               water for every grid cell. ASOS surface obs, 12-hourly upper-air
-              soundings, and gridded IEMRE reanalysis fill in the gaps. A 9-factor
-              composite score is written out for every 0.125° cell across CONUS,
-              for each hour of an 18-hour forecast.
+              soundings, and gridded IEMRE reanalysis fill in the gaps. A
+              10-factor composite score is written out for every 0.125° cell
+              across CONUS, for each hour of an 18-hour forecast.
             </li>
             <li>
               <strong>The contacts.</strong>
-              58k+ amateur microwave QSOs, each tagged with the atmosphere at
-              both ends of the path (and along it) at the time the contact
-              happened. That's a ground-truth dataset we can actually fit against
-              — "when you had this score, how far did the contact go, and did it
-              happen at all?"
+              {format_count(@stats.contacts)}+ amateur microwave QSOs, each
+              tagged with the atmosphere at both ends of the path (and along it)
+              at the time the contact happened. That's a ground-truth dataset we
+              can actually fit against — "when you had this score, how far did
+              the contact go, and did it happen at all?"
             </li>
           </ol>
           <p>
             The scoring is a weighted sum of ten factors: rain, humidity,
             precipitable water (PWAT), season, refractivity gradient, pressure,
-            T–Td depression, sky cover, wind, and time of day. Weights were
-            calibrated via gradient descent against 5,000 QSOs. The physics
-            changes by frequency: humidity helps at 10 GHz (more refractivity)
-            and hurts at 24+ GHz (absorption). Refractivity now uses native
-            HRRR hybrid-sigma levels (10–50 m resolution) for duct detection.
+            T–Td depression, sky cover, wind, and time of day — weights
+            recalibrated via gradient descent against the contact dataset. The
+            physics changes by frequency: humidity helps at 10 GHz (more
+            refractivity) and hurts at 24+ GHz (absorption). Refractivity uses
+            native HRRR hybrid-sigma levels (10–50 m resolution) for duct
+            detection, with a pressure-level fallback (~250 m) when the native
+            data isn't available.
           </p>
         </div>
 
@@ -233,12 +235,6 @@ defmodule MicrowavepropWeb.AboutLive do
   # percent, which is plenty for "big number on a marketing page."
   @estimate_tables ~w(hrrr_profiles propagation_scores surface_observations)
 
-  @stat_keys ~w(
-    contacts weather_stations surface_observations soundings hrrr_profiles
-    iemre_observations terrain_profiles propagation_scores beacons
-    commercial_samples
-  )a
-
   defp fetch_stats do
     %{
       contacts: count_exact("contacts"),
@@ -252,22 +248,25 @@ defmodule MicrowavepropWeb.AboutLive do
       beacons: count_exact("beacons"),
       commercial_samples: count_exact("commercial_samples")
     }
-  rescue
-    _ -> Map.new(@stat_keys, fn k -> {k, 0} end)
   end
 
+  # Each count is wrapped individually so a missing table in dev (or a
+  # transient query failure) never blanks the entire dashboard. The
+  # previous outer try/rescue zeroed all 10 numbers if any single one
+  # raised — every stat read 0 on environments lacking hrrr_profiles
+  # or propagation_scores.
   defp count_exact(table) do
-    %Postgrex.Result{rows: [[count]]} =
-      Repo.query!("SELECT count(*) FROM #{table}")
-
-    count
+    case Repo.query("SELECT count(*) FROM #{table}") do
+      {:ok, %Postgrex.Result{rows: [[count]]}} -> count
+      _ -> 0
+    end
   end
 
   defp count_estimate(table) when table in @estimate_tables do
-    %Postgrex.Result{rows: [[estimate]]} =
-      Repo.query!("SELECT reltuples::bigint FROM pg_class WHERE relname = $1", [table])
-
-    max(estimate || 0, 0)
+    case Repo.query("SELECT reltuples::bigint FROM pg_class WHERE relname = $1", [table]) do
+      {:ok, %Postgrex.Result{rows: [[estimate]]}} -> max(estimate || 0, 0)
+      _ -> 0
+    end
   end
 
   defp format_count(n) when is_integer(n) and n >= 1_000_000 do