Add CLAUDE.md and LaTeX paper, remove old papers directory

- Add CLAUDE.md with project guidance for Claude Code
- Add LaTeX/ with paper and figure generation scripts
- Remove papers/ directory (replaced by LaTeX/)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

LaTeX/generate_slipnet_graph.py

@@ -0,0 +1,140 @@
+"""
+Generate Slipnet graph visualization (Figure 1)
+Shows conceptual depth as node color gradient, with key Slipnet nodes and connections.
+"""
+
+import matplotlib.pyplot as plt
+import networkx as nx
+import numpy as np
+
+# Define key Slipnet nodes with their conceptual depths
+nodes = {
+    # Letters (depth 10)
+    'a': 10, 'b': 10, 'c': 10, 'd': 10, 'z': 10,
+    # Numbers (depth 30)
+    '1': 30, '2': 30, '3': 30,
+    # String positions (depth 40)
+    'leftmost': 40, 'rightmost': 40, 'middle': 40, 'single': 40,
+    # Directions (depth 40)
+    'left': 40, 'right': 40,
+    # Alphabetic positions (depth 60)
+    'first': 60, 'last': 60,
+    # Bond types (depth 50-80)
+    'predecessor': 50, 'successor': 50, 'sameness': 80,
+    # Group types (depth 50-80)
+    'predecessorGroup': 50, 'successorGroup': 50, 'samenessGroup': 80,
+    # Relations (depth 90)
+    'identity': 90, 'opposite': 90,
+    # Categories (depth 20-90)
+    'letterCategory': 30, 'stringPositionCategory': 70,
+    'directionCategory': 70, 'bondCategory': 80, 'length': 60,
+}
+
+# Define edges with their link lengths (inverse = strength)
+edges = [
+    # Letter to letterCategory
+    ('a', 'letterCategory', 97), ('b', 'letterCategory', 97),
+    ('c', 'letterCategory', 97), ('d', 'letterCategory', 97),
+    ('z', 'letterCategory', 97),
+
+    # Successor/predecessor relationships
+    ('a', 'b', 50), ('b', 'c', 50), ('c', 'd', 50),
+    ('b', 'a', 50), ('c', 'b', 50), ('d', 'c', 50),
+
+    # Bond types to bond category
+    ('predecessor', 'bondCategory', 60), ('successor', 'bondCategory', 60),
+    ('sameness', 'bondCategory', 30),
+
+    # Group types
+    ('sameness', 'samenessGroup', 30),
+    ('predecessor', 'predecessorGroup', 60),
+    ('successor', 'successorGroup', 60),
+
+    # Opposite relations
+    ('left', 'right', 80), ('right', 'left', 80),
+    ('first', 'last', 80), ('last', 'first', 80),
+
+    # Position relationships
+    ('left', 'directionCategory', 50), ('right', 'directionCategory', 50),
+    ('leftmost', 'stringPositionCategory', 50),
+    ('rightmost', 'stringPositionCategory', 50),
+    ('middle', 'stringPositionCategory', 50),
+
+    # Slippable connections
+    ('left', 'leftmost', 90), ('leftmost', 'left', 90),
+    ('right', 'rightmost', 90), ('rightmost', 'right', 90),
+    ('leftmost', 'first', 100), ('first', 'leftmost', 100),
+    ('rightmost', 'last', 100), ('last', 'rightmost', 100),
+
+    # Abstract relations
+    ('identity', 'bondCategory', 50),
+    ('opposite', 'bondCategory', 80),
+]
+
+# Create graph
+G = nx.DiGraph()
+
+# Add nodes with depth attribute
+for node, depth in nodes.items():
+    G.add_node(node, depth=depth)
+
+# Add edges with link length
+for source, target, length in edges:
+    G.add_edge(source, target, length=length, weight=100-length)
+
+# Create figure
+fig, ax = plt.subplots(figsize=(16, 12))
+
+# Use hierarchical layout based on depth
+pos = {}
+depth_groups = {}
+for node in G.nodes():
+    depth = G.nodes[node]['depth']
+    if depth not in depth_groups:
+        depth_groups[depth] = []
+    depth_groups[depth].append(node)
+
+# Position nodes by depth (y-axis) and spread horizontally
+for depth, node_list in depth_groups.items():
+    y = 1.0 - (depth / 100.0)  # Invert so shallow nodes at top
+    for i, node in enumerate(node_list):
+        x = (i - len(node_list)/2) / max(len(node_list), 10) * 2.5
+        pos[node] = (x, y)
+
+# Get node colors based on depth (blue=shallow/concrete, red=deep/abstract)
+node_colors = [G.nodes[node]['depth'] for node in G.nodes()]
+
+# Draw edges with thickness based on strength (inverse of link length)
+edges_to_draw = G.edges()
+edge_widths = [0.3 + (100 - G[u][v]['length']) / 100.0 * 3 for u, v in edges_to_draw]
+
+nx.draw_networkx_edges(G, pos, edgelist=edges_to_draw, width=edge_widths,
+                       alpha=0.3, arrows=True, arrowsize=10,
+                       connectionstyle='arc3,rad=0.1', ax=ax)
+
+# Draw nodes
+nx.draw_networkx_nodes(G, pos, node_color=node_colors,
+                       node_size=800, cmap='coolwarm',
+                       vmin=0, vmax=100, ax=ax)
+
+# Draw labels
+nx.draw_networkx_labels(G, pos, font_size=8, font_weight='bold', ax=ax)
+
+# Add colorbar
+sm = plt.cm.ScalarMappable(cmap='coolwarm',
+                           norm=plt.Normalize(vmin=0, vmax=100))
+sm.set_array([])
+cbar = plt.colorbar(sm, ax=ax, fraction=0.046, pad=0.04)
+cbar.set_label('Conceptual Depth', rotation=270, labelpad=20, fontsize=12)
+
+ax.set_title('Slipnet Graph Structure\n' +
+             'Color gradient: Blue (concrete/shallow) → Red (abstract/deep)\n' +
+             'Edge thickness: Link strength (inverse of link length)',
+             fontsize=14, fontweight='bold', pad=20)
+ax.axis('off')
+
+plt.tight_layout()
+plt.savefig('figure1_slipnet_graph.pdf', dpi=300, bbox_inches='tight')
+plt.savefig('figure1_slipnet_graph.png', dpi=300, bbox_inches='tight')
+print("Generated figure1_slipnet_graph.pdf and .png")
+plt.close()