将场加权标定模型接入回放分析

回放按声明的 30 帧加权空载窗口取基线并逐帧保存外推质量，field 模型单独进缓存键，实时入口拒绝。
新增测试覆盖窗口、质量与拒绝路径。全量门禁的 scene3d 两项失败与 studio 访问冲突为既有问题，
已归因并另立 studio-gate-hang。

shared/tests/test_analysis_force_validity.py

@@ -10,6 +10,8 @@ from __future__ import annotations
 
 import math
 
+import pytest
+
 from orisys_app_shared.analysis.model import ALGORITHM_VERSION, ForceSample
 from orisys_app_shared.analysis.service import AnalysisService
 
@@ -97,3 +99,45 @@ def test_results_stored_under_the_old_validity_rule_are_not_served():
     # Version 1 marked every frame invalid when the model lacked a zero; the cache key
     # carries this string, so those results must miss the cache and be recomputed.
     assert ALGORITHM_VERSION != "flow-hhd-contact-1"
+
+
+def test_extrapolated_fraction_is_quality_not_validity():
+    """A field estimate's extrapolation is evidence about its support, not validity.
+
+    The SDK reports the field model's extrapolated/coverage fraction in
+    ``calibration_diagnostics`` and keeps the per-axis status ``ok``; the app stores
+    the fractions as quality and must keep the newton value. Reading them as
+    invalidity would silently drop every experimental value.
+    """
+    reading = _reading({"fn": "ok"}, normal=3.5)
+    reading["calibration_diagnostics"] = {
+        "extrapolated_fraction": 0.42,
+        "coverage_fraction": 0.9,
+        "baseline_N": 0.25,
+        "model_fingerprint": "f" * 64,
+    }
+    sample = ForceSample.from_reading(reading)
+    assert sample.normal == pytest.approx(3.5)
+    assert sample.valid
+    assert sample.diagnostics["extrapolated_fraction"] == pytest.approx(0.42)
+    assert sample.field_quality() == pytest.approx((0.42, 0.9))
+
+    # The force payload is unchanged by the new evidence: quality is stored in its
+    # own frame payload, so an older result and this one read the same force fields.
+    decoded = ForceSample.decode(sample.encode())
+    assert decoded.normal == pytest.approx(3.5)
+    assert decoded.diagnostics == {}
+
+
+def test_a_baseline_wait_still_keeps_the_raw_measurement():
+    """The first 30 declared frames are ``zero_unavailable``: raw, not newton."""
+    reading = _reading({"fn": "zero_unavailable"}, normal=float("nan"))
+    reading["calibration_diagnostics"] = {
+        "pending_reference_frames": 7,
+        "extrapolated_fraction": 0.35,
+    }
+    sample = ForceSample.from_reading(reading)
+    assert sample.valid
+    assert sample.raw() == (1234.0, -5.0, 7.0)
+    assert math.isnan(sample.normal)
+    assert sample.diagnostics["pending_reference_frames"] == 7