fix(controller): re-arm window_drop and expose kernel_datapath

Three fixes from live-calibrating the kernel impairment filters on an
isolated instance (Docker-to-Docker veth link, per-sequence evidence):

- update_filters skipped an unchanged filters dict as a no-op, so a
  one-shot window_drop outage that had already passed could never be
  re-armed: re-applying the same values produced no datapath command at
  all. A PUT still carrying window_drop now reconciles, restarting the
  schedule from the apply as documented. Measured: identical re-apply
  moves the outage window from seq 50-70 to 70-91 (arm at +8s of the
  new apply).

- gemodel parameter semantics were documented backwards in the
  validation rules, available_filters, the MCP/copilot descriptions and
  the feature docs. Measured against the kernel (per-direction counters,
  offered = sent + dropped): p is the good-to-bad transition chance, r
  the bad-to-good transition, 1-h the loss chance in the bad state (the
  good state loses nothing) - mean one-way loss p/(p+r)*(1-h), e.g.
  [10,30,100] -> 24.8%/25.7% measured vs 25% predicted, [5,45,100] ->
  10.8% both ways vs 10%.

- kernel_datapath was silently stripped from every REST/MCP link payload
  by the response model (LinkBase carried no such field), so clients
  could not tell a kernel link from a relay one.

Also verified on the same setup: the 3-argument window_drop form works
exactly as specified ([3000,5000,100] -> a single seq 31-55 outage,
[20000,6000,100] -> seq 115-144), and both generations of the command
builder emit the parameters unpadded.

Adds an API test for the field and controller tests for the no-op skip
and the window_drop re-arm exemption.

gns3server/controller/link.py

@@ -105,12 +105,14 @@ FILTERS = [
     {
         "type": "gemodel",
         "name": "Gilbert-Elliot loss",
-        "description": "Bursty loss model: p is the loss chance in the bad state, r in the good state, 1-h the "
-        "chance of moving from good to bad. Mutually exclusive with packet loss; kernel-datapath links only",
+        "description": "Bursty loss model: p is the chance of moving from the good to the bad state, r the chance "
+        "of moving back, and 1-h the loss chance while in the bad state (the good state loses nothing) — the "
+        "steady-state mean loss is p/(p+r) x (1-h). Mutually exclusive with packet loss; kernel-datapath links "
+        "only",
         "parameters": [
-            {"name": "p (bad-state loss)", "minimum": 0, "maximum": 100, "type": "int", "unit": "%"},
-            {"name": "r (good-state loss)", "minimum": 0, "maximum": 100, "type": "int", "unit": "%"},
-            {"name": "1-h (good-to-bad)", "minimum": 0, "maximum": 100, "type": "int", "unit": "%"},
+            {"name": "p (good-to-bad)", "minimum": 0, "maximum": 100, "type": "int", "unit": "%"},
+            {"name": "r (bad-to-good)", "minimum": 0, "maximum": 100, "type": "int", "unit": "%"},
+            {"name": "1-h (bad-state loss)", "minimum": 0, "maximum": 100, "type": "int", "unit": "%"},
         ],
     },
     {
@@ -338,7 +340,12 @@ class Link:
                     )
                 )
 
-        if new_filters != self.filters:
+        # An unchanged filters dict is normally a no-op skip, but a PUT that
+        # still carries window_drop must reconcile: the outage schedule is
+        # measured from the apply, so re-sending the same window has to
+        # re-arm the one-shot outage (the documented contract is that any
+        # filter update restarts the schedule).
+        if new_filters != self.filters or "window_drop" in new_filters:
             self._filters = new_filters
             if self._created:
                 await self.update()