feat(explorer): add scree plot and clean up SVD axis chart

- Add load_scree_data() cached loader computing L2-norm of party scores
  per SVD dimension as a proxy for component importance
- Add _render_scree_plot() rendering a bar chart of the first 15 components
- Insert scree plot + Dutch explanation at the top of build_svd_components_tab
- Clean up _render_party_axis_chart: remove tick numbers, axis line, grid,
  and zero-line from the x-axis (pole labels remain as chart title)

explorer.py

@@ -250,6 +250,102 @@ def load_party_axis_scores(db_path: str) -> Dict[str, List[float]]:
             pass
 
 
+@st.cache_data(show_spinner="Scree-plot laden…")
+def load_scree_data(db_path: str) -> List[float]:
+    """Return a list of component importances (L2-norm of party scores per dimension).
+
+    Uses the same svd_vectors data as load_party_axis_scores but aggregates across
+    all components (0-indexed). Returns a list of length == vector dimensionality (50).
+    """
+    try:
+        con = duckdb.connect(database=db_path, read_only=True)
+        party_list = sorted(CURRENT_PARLIAMENT_PARTIES)
+        placeholders = ", ".join("?" for _ in party_list)
+        rows = con.execute(
+            f"SELECT vector FROM svd_vectors "
+            f"WHERE entity_type='mp' AND window_id='current_parliament' "
+            f"AND entity_id IN ({placeholders})",
+            party_list,
+        ).fetchall()
+        vectors: List[List[float]] = []
+        for (raw_vec,) in rows:
+            if isinstance(raw_vec, str):
+                vec = json.loads(raw_vec)
+            elif isinstance(raw_vec, (bytes, bytearray)):
+                vec = json.loads(raw_vec.decode())
+            elif isinstance(raw_vec, list):
+                vec = raw_vec
+            else:
+                try:
+                    vec = list(raw_vec)
+                except Exception:
+                    continue
+            vectors.append([float(v) if v is not None else 0.0 for v in vec])
+        if not vectors:
+            return []
+        n_dims = len(vectors[0])
+        importances: List[float] = []
+        for dim in range(n_dims):
+            col = [v[dim] for v in vectors if dim < len(v)]
+            l2 = sum(x**2 for x in col) ** 0.5
+            importances.append(l2)
+        return importances
+    except Exception:
+        logger.exception("Failed to load scree data")
+        return []
+    finally:
+        try:
+            con.close()
+        except Exception:
+            pass
+
+
+def _render_scree_plot(importances: List[float], n_show: int = 15) -> None:
+    """Render a bar chart showing relative component importance (scree plot).
+
+    Args:
+        importances: List of L2-norm scores per component (0-indexed).
+        n_show: How many components to display (default: first 15).
+    """
+    if not importances:
+        return
+    data = importances[:n_show]
+    components = list(range(1, len(data) + 1))
+    colours = [
+        PARTY_COLOURS.get("PVV", "#1565C0") if i == 0 else "#90CAF9"
+        for i in range(len(data))
+    ]
+    fig = go.Figure(
+        go.Bar(
+            x=components,
+            y=data,
+            marker_color=colours,
+            hovertemplate="As %{x}<br>Gewicht: %{y:.2f}<extra></extra>",
+        )
+    )
+    fig.update_layout(
+        height=220,
+        margin={"l": 10, "r": 10, "t": 10, "b": 30},
+        xaxis={
+            "title": "SVD-as",
+            "tickmode": "linear",
+            "tick0": 1,
+            "dtick": 1,
+            "showline": False,
+            "showgrid": False,
+        },
+        yaxis={
+            "title": "Relatief gewicht",
+            "showline": False,
+            "showgrid": True,
+            "gridcolor": "#eeeeee",
+        },
+        plot_bgcolor="rgba(0,0,0,0)",
+        paper_bgcolor="rgba(0,0,0,0)",
+    )
+    st.plotly_chart(fig, use_container_width=True)
+
+
 def _render_party_axis_chart(
     party_scores: Dict[str, List[float]], comp_sel: int, theme: dict
 ) -> None:
@@ -322,8 +418,10 @@ def _render_party_axis_chart(
         margin={"l": 10, "r": 10, "t": 10, "b": 30},
         xaxis={
             "title": f"← {left_label}  |  {right_label} →",
-            "zeroline": True,
+            "showticklabels": False,
-            "zerolinecolor": "#aaaaaa",
+            "showline": False,
+            "showgrid": False,
+            "zeroline": False,
         },
         yaxis={"visible": False, "range": [-1, 2]},
         plot_bgcolor="rgba(0,0,0,0)",
@@ -957,6 +1055,16 @@ def build_svd_components_tab(db_path: str) -> None:
         "het spanningsveld dat de as beschrijft."
     )
 
+    # Scree plot: relative importance of each SVD component
+    scree_importances = load_scree_data(db_path)
+    if scree_importances:
+        st.markdown(
+            "**Scree-plot** — het relatieve gewicht van elke SVD-as. "
+            "De eerste assen verklaren het meeste van de stemverschillen in de Kamer; "
+            "latere assen zijn subtieler maar politiek nog steeds betekenisvol."
+        )
+        _render_scree_plot(scree_importances)
+
     json_path = os.path.join("thoughts", "explorer", "top_svd_top_motions.json")
     if not os.path.exists(json_path):
         st.warning(