Remove Paper stats tab; explain F_n/M_n in Factor poster; show mode-label preview in factor dropdown

app.py

@@ -1329,10 +1329,26 @@ def _gallery_axes(figsize=(10, 9)):
 # ---------- (1) Factor decomposition poster ----------
 
 def factor_options(sibling: str):
+    """Return list of (descriptive_label, factor_id) tuples for the factor dropdown."""
     m = MODELS[sibling]
-    fids = sorted({md.property for md in m.modes if md.kind == "factor"},
-                  key=lambda x: int(x.split("_")[-1]) if x.split("_")[-1].isdigit() else 99)
-    return fids
+    by_fid: dict[str, list] = {}
+    for md in m.modes:
+        if md.kind != "factor": continue
+        by_fid.setdefault(md.property, []).append(md.label)
+    def sort_key(fid):
+        last = fid.split("_")[-1]
+        return int(last) if last.isdigit() else 999
+    out = []
+    for fid in sorted(by_fid.keys(), key=sort_key):
+        labels = by_fid[fid]
+        # Take first 2-3 mode-label keywords as a preview
+        preview = " · ".join(lab[:32] for lab in labels[:2])
+        out.append((f"{fid}  —  {preview}", fid))
+    return out
+
+def factor_id_list(sibling: str):
+    """Just the bare F_n IDs, for the actual handler input."""
+    return [fid for _, fid in factor_options(sibling)]
 
 def render_factor_poster(sibling: str, factor_id: str):
     """Reference-screenshot style: dark teal background, faint contour texture,
@@ -2162,28 +2178,38 @@ Three sibling ingredient embeddings from [arXiv:2605.22391](https://arxiv.org/ab
                 label="Try one of these baskets",
             )
 
-        # ---------- Tab: PAPER STATS ----------
-        with gr.Tab("Paper stats"):
-            gr.Markdown("Headline numbers from the paper §3.2. The Cooc < Core < Chem ordering on every probe stratum.")
-            dq_plot = gr.Plot(value=render_direction_quality_heatmap(), label="")
-
         # ---------- Tab 5: GALLERY ----------
         with gr.Tab("Gallery"):
             gr.Markdown("Six aesthetic views of the model. All rendered in the Kaikaku palette.")
             with gr.Tabs():
                 # --- Factor poster ---
                 with gr.Tab("Factor poster"):
+                    gr.Markdown(
+                        "**How to read this.** Each sibling has **20 emergent ICA factors** (`F_0` to `F_19`), "
+                        "ranked by stability across random seeds (`F_0` is most reproducible). "
+                        "A factor is an unsupervised latent dimension discovered by FastICA on the embedding "
+                        "with food-group variance projected out. "
+                        "Each factor's top-quartile ingredients are partitioned into **3-7 GMM modes** "
+                        "(`M0`, `M1`, ...) — culinary neighbourhoods along that factor. "
+                        "Mode labels (e.g. *Chinese Wok Essentials*) are Claude-generated from member contents. "
+                        "Pick a factor below; the dropdown shows a preview of its mode labels."
+                    )
+                    _fp_choices = factor_options("chem")
+                    _fp_default = _fp_choices[0][1] if _fp_choices else ""
                     with gr.Row():
                         fp_sib = gr.Radio(choices=["cooc","core","chem"], value="chem",
                                           label="Sibling", scale=1)
-                        fp_factor = gr.Dropdown(choices=factor_options("chem"),
-                                                value=factor_options("chem")[0] if factor_options("chem") else None,
-                                                label="Factor", scale=2)
+                        fp_factor = gr.Dropdown(choices=_fp_choices,
+                                                value=_fp_default,
+                                                label="Factor (preview of mode labels shown)", scale=3)
                         fp_btn = gr.Button("Render", variant="primary", scale=1)
-                    fp_plot = gr.Plot(label="", value=render_factor_poster("chem", factor_options("chem")[0] if factor_options("chem") else ""))
+                    fp_plot = gr.Plot(label="", value=render_factor_poster("chem", _fp_default))
                     fp_btn.click(render_factor_poster, inputs=[fp_sib, fp_factor], outputs=fp_plot, show_progress="full")
-                    fp_sib.change(lambda s: gr.Dropdown(choices=factor_options(s), value=factor_options(s)[0] if factor_options(s) else None),
-                                  inputs=fp_sib, outputs=fp_factor)
+                    def _refresh_factor_choices(s):
+                        choices = factor_options(s)
+                        return gr.Dropdown(choices=choices, value=choices[0][1] if choices else None)
+                    fp_sib.change(_refresh_factor_choices, inputs=fp_sib, outputs=fp_factor)
+                    fp_factor.change(render_factor_poster, inputs=[fp_sib, fp_factor], outputs=fp_plot, show_progress="minimal")
 
                 # --- Cuisine compass ---
                 with gr.Tab("Cuisine compass"):