Upload experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence (part 10)

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0575_01/3642.json

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+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0575_01",
+ "dataset": "scannet",
+ "question_id": 3642,
+ "question_type": "object_rel_direction_hard",
+ "question": "If I am standing by the door and facing the trash bin, is the table to my front-left, front-right, back-left, or back-right?\nThe directions refer to the quadrants of a Cartesian plane (if I am standing at the origin and facing along the positive y-axis).",
+ "options": [
+  "A. back-right",
+  "B. back-left",
+  "C. front-left",
+  "D. front-right"
+ ],
+ "full_prompt": null,
+ "answer_expected": "D",
+ "answer_given": "D",
+ "answer_raw": "D",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0575_01/3643.json

@@ -0,0 +1,25 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0575_01",
+ "dataset": "scannet",
+ "question_id": 3643,
+ "question_type": "object_rel_direction_hard",
+ "question": "If I am standing by the door and facing the table, is the trash bin to my front-left, front-right, back-left, or back-right?\nThe directions refer to the quadrants of a Cartesian plane (if I am standing at the origin and facing along the positive y-axis).",
+ "options": [
+  "A. back-right",
+  "B. front-left",
+  "C. front-right",
+  "D. back-left"
+ ],
+ "full_prompt": null,
+ "answer_expected": "B",
+ "answer_given": "B",
+ "answer_raw": "B",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0575_01/3644.json

@@ -0,0 +1,25 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0575_01",
+ "dataset": "scannet",
+ "question_id": 3644,
+ "question_type": "object_rel_direction_hard",
+ "question": "If I am standing by the trash bin and facing the door, is the table to my front-left, front-right, back-left, or back-right?\nThe directions refer to the quadrants of a Cartesian plane (if I am standing at the origin and facing along the positive y-axis).",
+ "options": [
+  "A. front-right",
+  "B. back-right",
+  "C. front-left",
+  "D. back-left"
+ ],
+ "full_prompt": null,
+ "answer_expected": "C",
+ "answer_given": "C",
+ "answer_raw": "C",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0575_01/3818.json

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+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0575_01",
+ "dataset": "scannet",
+ "question_id": 3818,
+ "question_type": "room_size_estimation",
+ "question": "What is the size of this room (in square meters)? \nIf multiple rooms are shown, estimate the size of the combined space.",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "21.2",
+ "answer_given": "21.3",
+ "answer_raw": "21.3",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0575_01/4321.json

@@ -0,0 +1,24 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0575_01",
+ "dataset": "scannet",
+ "question_id": 4321,
+ "question_type": "object_rel_direction_medium",
+ "question": "If I am standing by the door and facing the trash bin, is the table to my left, right, or back?\nAn object is to my back if I would have to turn at least 135 degrees in order to face it.",
+ "options": [
+  "A. back",
+  "B. left",
+  "C. right"
+ ],
+ "full_prompt": null,
+ "answer_expected": "C",
+ "answer_given": "C",
+ "answer_raw": "C",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0575_01/4322.json

@@ -0,0 +1,24 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0575_01",
+ "dataset": "scannet",
+ "question_id": 4322,
+ "question_type": "object_rel_direction_medium",
+ "question": "If I am standing by the door and facing the table, is the trash bin to my left, right, or back?\nAn object is to my back if I would have to turn at least 135 degrees in order to face it.",
+ "options": [
+  "A. right",
+  "B. left",
+  "C. back"
+ ],
+ "full_prompt": null,
+ "answer_expected": "B",
+ "answer_given": "B",
+ "answer_raw": "B",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0575_01/4323.json

@@ -0,0 +1,24 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0575_01",
+ "dataset": "scannet",
+ "question_id": 4323,
+ "question_type": "object_rel_direction_medium",
+ "question": "If I am standing by the trash bin and facing the door, is the table to my left, right, or back?\nAn object is to my back if I would have to turn at least 135 degrees in order to face it.",
+ "options": [
+  "A. left",
+  "B. right",
+  "C. back"
+ ],
+ "full_prompt": null,
+ "answer_expected": "A",
+ "answer_given": "A",
+ "answer_raw": "A",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0575_01/4524.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0575_01",
+ "dataset": "scannet",
+ "question_id": 4524,
+ "question_type": "object_counting",
+ "question": "How many chair(s) are in this room?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "10",
+ "answer_given": "10",
+ "answer_raw": "10",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0575_01/4525.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0575_01",
+ "dataset": "scannet",
+ "question_id": 4525,
+ "question_type": "object_counting",
+ "question": "How many tv(s) are in this room?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "2",
+ "answer_given": "2",
+ "answer_raw": "2",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0575_01/4820.json

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+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0575_01",
+ "dataset": "scannet",
+ "question_id": 4820,
+ "question_type": "object_abs_distance",
+ "question": "Measuring from the closest point of each object, what is the distance between the trash bin and the window (in meters)?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "1.4",
+ "answer_given": "",
+ "answer_raw": "",
+ "score": 0.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0575_01/4821.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0575_01",
+ "dataset": "scannet",
+ "question_id": 4821,
+ "question_type": "object_abs_distance",
+ "question": "Measuring from the closest point of each object, what is the distance between the trash bin and the door (in meters)?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "1.1",
+ "answer_given": "1.27",
+ "answer_raw": "1.27",
+ "score": 0.7
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0575_01/4822.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0575_01",
+ "dataset": "scannet",
+ "question_id": 4822,
+ "question_type": "object_abs_distance",
+ "question": "Measuring from the closest point of each object, what is the distance between the table and the window (in meters)?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "1.1",
+ "answer_given": "",
+ "answer_raw": "",
+ "score": 0.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0575_01/4823.json

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+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0575_01",
+ "dataset": "scannet",
+ "question_id": 4823,
+ "question_type": "object_abs_distance",
+ "question": "Measuring from the closest point of each object, what is the distance between the table and the door (in meters)?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "1.2",
+ "answer_given": "1.45",
+ "answer_raw": "1.45",
+ "score": 0.6
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0575_01/4824.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0575_01",
+ "dataset": "scannet",
+ "question_id": 4824,
+ "question_type": "object_abs_distance",
+ "question": "Measuring from the closest point of each object, what is the distance between the table and the trash bin (in meters)?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "1.2",
+ "answer_given": "1.29",
+ "answer_raw": "1.29",
+ "score": 0.9
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0575_01/5097.json

@@ -0,0 +1,24 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0575_01",
+ "dataset": "scannet",
+ "question_id": 5097,
+ "question_type": "route_planning",
+ "question": "You are a robot beginning at the corner of the white wall and the brown wall, facing the glass door. You want to navigate to the green chair closest to the TVs. You will perform the following actions (Note: for each [please fill in], choose either 'turn back,' 'turn left,' or 'turn right.'): 1. Go forward until the glass door 2. [please fill in] 3. Go forward until the green chair. You have reached the final destination.",
+ "options": [
+  "A. Turn Left",
+  "B. Turn Right",
+  "C. Turn Back"
+ ],
+ "full_prompt": null,
+ "answer_expected": "A",
+ "answer_given": "",
+ "answer_raw": "",
+ "score": 0.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0575_01/_aggregate.json

@@ -0,0 +1,15 @@
+{
+ "scene_id": "scene0575_01",
+ "aggregate": {
+  "overall": 56.76190476190476,
+  "object_counting_MRA:.5:.95:.05": 100.0,
+  "object_abs_distance_MRA:.5:.95:.05": 43.99999999999999,
+  "object_size_estimation_MRA:.5:.95:.05": 20.0,
+  "room_size_estimation_MRA:.5:.95:.05": 100.0,
+  "object_rel_distance_accuracy": 66.66666666666666,
+  "object_rel_direction_accuracy": 66.66666666666666,
+  "route_planning_accuracy": 0.0,
+  "tabulated_keys": "overall, object_counting_MRA:.5:.95:.05, object_abs_distance_MRA:.5:.95:.05, object_size_estimation_MRA:.5:.95:.05, room_size_estimation_MRA:.5:.95:.05, object_rel_distance_accuracy, object_rel_direction_accuracy, route_planning_accuracy",
+  "tabulated_results": "56.762, 100.000, 44.000, 20.000, 100.000, 66.667, 66.667, 0.000"
+ }
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/3113.json

@@ -0,0 +1,25 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 3113,
+ "question_type": "object_rel_distance",
+ "question": "Measuring from the closest point of each object, which of these objects (lamp, mirror, backpack, table) is the closest to the bookshelf?",
+ "options": [
+  "A. lamp",
+  "B. mirror",
+  "C. backpack",
+  "D. table"
+ ],
+ "full_prompt": null,
+ "answer_expected": "B",
+ "answer_given": "D",
+ "answer_raw": "D",
+ "score": 0.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/3114.json

@@ -0,0 +1,25 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 3114,
+ "question_type": "object_rel_distance",
+ "question": "Measuring from the closest point of each object, which of these objects (trash bin, pillow, bed, lamp) is the closest to the table?",
+ "options": [
+  "A. trash bin",
+  "B. pillow",
+  "C. bed",
+  "D. lamp"
+ ],
+ "full_prompt": null,
+ "answer_expected": "C",
+ "answer_given": "A",
+ "answer_raw": "A",
+ "score": 0.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/3424.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 3424,
+ "question_type": "object_size_estimation",
+ "question": "What is the length of the longest dimension (length, width, or height) of the bed, measured in centimeters?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "223",
+ "answer_given": "105.0",
+ "answer_raw": "105.0",
+ "score": 0.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/3425.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 3425,
+ "question_type": "object_size_estimation",
+ "question": "What is the length of the longest dimension (length, width, or height) of the chair, measured in centimeters?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "93",
+ "answer_given": "66.0",
+ "answer_raw": "66.0",
+ "score": 0.5
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/3426.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 3426,
+ "question_type": "object_size_estimation",
+ "question": "What is the length of the longest dimension (length, width, or height) of the window, measured in centimeters?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "206",
+ "answer_given": "94.0",
+ "answer_raw": "94.0",
+ "score": 0.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/3427.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 3427,
+ "question_type": "object_size_estimation",
+ "question": "What is the length of the longest dimension (length, width, or height) of the bookshelf, measured in centimeters?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "202",
+ "answer_given": "98.0",
+ "answer_raw": "98.0",
+ "score": 0.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/3428.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 3428,
+ "question_type": "object_size_estimation",
+ "question": "What is the length of the longest dimension (length, width, or height) of the lamp, measured in centimeters?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "79",
+ "answer_given": "66.0",
+ "answer_raw": "66.0",
+ "score": 0.7
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/3429.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 3429,
+ "question_type": "object_size_estimation",
+ "question": "What is the length of the longest dimension (length, width, or height) of the nightstand, measured in centimeters?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "69",
+ "answer_given": "53.0",
+ "answer_raw": "53.0",
+ "score": 0.6
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/3430.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 3430,
+ "question_type": "object_size_estimation",
+ "question": "What is the length of the longest dimension (length, width, or height) of the mirror, measured in centimeters?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "103",
+ "answer_given": "164.0",
+ "answer_raw": "164.0",
+ "score": 0.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/3431.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 3431,
+ "question_type": "object_size_estimation",
+ "question": "What is the length of the longest dimension (length, width, or height) of the trash bin, measured in centimeters?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "31",
+ "answer_given": "35.0",
+ "answer_raw": "35.0",
+ "score": 0.8
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/3432.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 3432,
+ "question_type": "object_size_estimation",
+ "question": "What is the length of the longest dimension (length, width, or height) of the table, measured in centimeters?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "63",
+ "answer_given": "57.0",
+ "answer_raw": "57.0",
+ "score": 0.9
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/3645.json

@@ -0,0 +1,25 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 3645,
+ "question_type": "object_rel_direction_hard",
+ "question": "If I am standing by the window and facing the lamp, is the trash bin to my front-left, front-right, back-left, or back-right?\nThe directions refer to the quadrants of a Cartesian plane (if I am standing at the origin and facing along the positive y-axis).",
+ "options": [
+  "A. front-right",
+  "B. front-left",
+  "C. back-left",
+  "D. back-right"
+ ],
+ "full_prompt": null,
+ "answer_expected": "C",
+ "answer_given": "C",
+ "answer_raw": "C",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/3646.json

@@ -0,0 +1,25 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 3646,
+ "question_type": "object_rel_direction_hard",
+ "question": "If I am standing by the lamp and facing the window, is the trash bin to my front-left, front-right, back-left, or back-right?\nThe directions refer to the quadrants of a Cartesian plane (if I am standing at the origin and facing along the positive y-axis).",
+ "options": [
+  "A. front-left",
+  "B. back-left",
+  "C. back-right",
+  "D. front-right"
+ ],
+ "full_prompt": null,
+ "answer_expected": "D",
+ "answer_given": "D",
+ "answer_raw": "D",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/3819.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 3819,
+ "question_type": "room_size_estimation",
+ "question": "What is the size of this room (in square meters)? \nIf multiple rooms are shown, estimate the size of the combined space.",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "9.3",
+ "answer_given": "9.9",
+ "answer_raw": "9.9",
+ "score": 0.9
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/4050.json

@@ -0,0 +1,25 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 4050,
+ "question_type": "obj_appearance_order",
+ "question": "What will be the first-time appearance order of the following categories in the video: window, table, chair, bed?",
+ "options": [
+  "A. bed, chair, table, window",
+  "B. bed, window, chair, table",
+  "C. window, bed, chair, table",
+  "D. window, table, chair, bed"
+ ],
+ "full_prompt": null,
+ "answer_expected": "A",
+ "answer_given": "A",
+ "answer_raw": "A",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/4051.json

@@ -0,0 +1,38 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 4051,
+ "question_type": "obj_appearance_order",
+ "question": "What will be the first-time appearance order of the following categories in the video: trash bin, table, pillow, mirror?",
+ "options": [
+  "A. trash bin, table, mirror, pillow",
+  "B. pillow, table, mirror, trash bin",
+  "C. pillow, table, trash bin, mirror",
+  "D. trash bin, table, pillow, mirror"
+ ],
+ "full_prompt": null,
+ "answer_expected": "B",
+ "answer_given": "C",
+ "answer_raw": "C",
+ "score": 0.0,
+ "appearance_order_diagnosis": {
+  "diagnosable": true,
+  "class_positions_in_real_order": {
+   "trash bin": 7,
+   "table": 9,
+   "pillow": 5,
+   "mirror": 8
+  },
+  "true_order_per_spatial_code": "pillow, trash bin, mirror, table",
+  "ground_truth_option_text": "pillow, table, mirror, trash bin",
+  "matches_ground_truth": false,
+  "verdict": "the spatial code's real detected order genuinely disagrees with the official ground truth's ordering -- not an engine bug, the engine correctly read the real data it had"
+ }
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/4052.json

@@ -0,0 +1,38 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 4052,
+ "question_type": "obj_appearance_order",
+ "question": "What will be the first-time appearance order of the following categories in the video: bookshelf, mirror, lamp, table?",
+ "options": [
+  "A. bookshelf, mirror, lamp, table",
+  "B. lamp, table, mirror, bookshelf",
+  "C. lamp, mirror, table, bookshelf",
+  "D. lamp, table, bookshelf, mirror"
+ ],
+ "full_prompt": null,
+ "answer_expected": "D",
+ "answer_given": "C",
+ "answer_raw": "C",
+ "score": 0.0,
+ "appearance_order_diagnosis": {
+  "diagnosable": true,
+  "class_positions_in_real_order": {
+   "bookshelf": 12,
+   "mirror": 8,
+   "lamp": 4,
+   "table": 9
+  },
+  "true_order_per_spatial_code": "lamp, mirror, table, bookshelf",
+  "ground_truth_option_text": "lamp, table, bookshelf, mirror",
+  "matches_ground_truth": false,
+  "verdict": "the spatial code's real detected order genuinely disagrees with the official ground truth's ordering -- not an engine bug, the engine correctly read the real data it had"
+ }
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/4053.json

@@ -0,0 +1,38 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 4053,
+ "question_type": "obj_appearance_order",
+ "question": "What will be the first-time appearance order of the following categories in the video: mirror, trash bin, chair, bookshelf?",
+ "options": [
+  "A. chair, bookshelf, trash bin, mirror",
+  "B. mirror, trash bin, chair, bookshelf",
+  "C. bookshelf, mirror, trash bin, chair",
+  "D. chair, bookshelf, mirror, trash bin"
+ ],
+ "full_prompt": null,
+ "answer_expected": "D",
+ "answer_given": "B",
+ "answer_raw": "B",
+ "score": 0.0,
+ "appearance_order_diagnosis": {
+  "diagnosable": true,
+  "class_positions_in_real_order": {
+   "mirror": 8,
+   "trash bin": 7,
+   "chair": 14,
+   "bookshelf": 12
+  },
+  "true_order_per_spatial_code": "trash bin, mirror, bookshelf, chair",
+  "ground_truth_option_text": "chair, bookshelf, mirror, trash bin",
+  "matches_ground_truth": false,
+  "verdict": "the spatial code's real detected order genuinely disagrees with the official ground truth's ordering -- not an engine bug, the engine correctly read the real data it had"
+ }
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/4054.json

@@ -0,0 +1,25 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 4054,
+ "question_type": "obj_appearance_order",
+ "question": "What will be the first-time appearance order of the following categories in the video: mirror, chair, lamp, window?",
+ "options": [
+  "A. chair, window, mirror, lamp",
+  "B. lamp, chair, window, mirror",
+  "C. mirror, chair, lamp, window",
+  "D. chair, mirror, window, lamp"
+ ],
+ "full_prompt": null,
+ "answer_expected": "B",
+ "answer_given": "B",
+ "answer_raw": "B",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/4055.json

@@ -0,0 +1,38 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 4055,
+ "question_type": "obj_appearance_order",
+ "question": "What will be the first-time appearance order of the following categories in the video: backpack, mirror, table, bookshelf?",
+ "options": [
+  "A. backpack, table, bookshelf, mirror",
+  "B. backpack, mirror, table, bookshelf",
+  "C. mirror, backpack, table, bookshelf",
+  "D. mirror, bookshelf, backpack, table"
+ ],
+ "full_prompt": null,
+ "answer_expected": "A",
+ "answer_given": "C",
+ "answer_raw": "C",
+ "score": 0.0,
+ "appearance_order_diagnosis": {
+  "diagnosable": true,
+  "class_positions_in_real_order": {
+   "backpack": 13,
+   "mirror": 8,
+   "table": 9,
+   "bookshelf": 12
+  },
+  "true_order_per_spatial_code": "mirror, table, bookshelf, backpack",
+  "ground_truth_option_text": "backpack, table, bookshelf, mirror",
+  "matches_ground_truth": false,
+  "verdict": "the spatial code's real detected order genuinely disagrees with the official ground truth's ordering -- not an engine bug, the engine correctly read the real data it had"
+ }
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/4056.json

@@ -0,0 +1,38 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 4056,
+ "question_type": "obj_appearance_order",
+ "question": "What will be the first-time appearance order of the following categories in the video: lamp, table, chair, window?",
+ "options": [
+  "A. window, table, chair, lamp",
+  "B. lamp, table, chair, window",
+  "C. lamp, chair, table, window",
+  "D. table, window, lamp, chair"
+ ],
+ "full_prompt": null,
+ "answer_expected": "C",
+ "answer_given": "B",
+ "answer_raw": "B",
+ "score": 0.0,
+ "appearance_order_diagnosis": {
+  "diagnosable": true,
+  "class_positions_in_real_order": {
+   "lamp": 4,
+   "table": 9,
+   "chair": 14,
+   "window": 10
+  },
+  "true_order_per_spatial_code": "lamp, table, window, chair",
+  "ground_truth_option_text": "lamp, chair, table, window",
+  "matches_ground_truth": false,
+  "verdict": "the spatial code's real detected order genuinely disagrees with the official ground truth's ordering -- not an engine bug, the engine correctly read the real data it had"
+ }
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/4057.json

@@ -0,0 +1,38 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 4057,
+ "question_type": "obj_appearance_order",
+ "question": "What will be the first-time appearance order of the following categories in the video: table, chair, trash bin, window?",
+ "options": [
+  "A. window, trash bin, table, chair",
+  "B. chair, table, window, trash bin",
+  "C. table, chair, trash bin, window",
+  "D. chair, table, trash bin, window"
+ ],
+ "full_prompt": null,
+ "answer_expected": "B",
+ "answer_given": "A",
+ "answer_raw": "A",
+ "score": 0.0,
+ "appearance_order_diagnosis": {
+  "diagnosable": true,
+  "class_positions_in_real_order": {
+   "table": 9,
+   "chair": 14,
+   "trash bin": 7,
+   "window": 10
+  },
+  "true_order_per_spatial_code": "trash bin, table, window, chair",
+  "ground_truth_option_text": "chair, table, window, trash bin",
+  "matches_ground_truth": false,
+  "verdict": "the spatial code's real detected order genuinely disagrees with the official ground truth's ordering -- not an engine bug, the engine correctly read the real data it had"
+ }
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/4058.json

@@ -0,0 +1,38 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 4058,
+ "question_type": "obj_appearance_order",
+ "question": "What will be the first-time appearance order of the following categories in the video: table, nightstand, trash bin, chair?",
+ "options": [
+  "A. table, trash bin, chair, nightstand",
+  "B. trash bin, nightstand, chair, table",
+  "C. table, nightstand, trash bin, chair",
+  "D. nightstand, chair, table, trash bin"
+ ],
+ "full_prompt": null,
+ "answer_expected": "D",
+ "answer_given": "B",
+ "answer_raw": "B",
+ "score": 0.0,
+ "appearance_order_diagnosis": {
+  "diagnosable": true,
+  "class_positions_in_real_order": {
+   "table": 9,
+   "nightstand": 3,
+   "trash bin": 7,
+   "chair": 14
+  },
+  "true_order_per_spatial_code": "nightstand, trash bin, table, chair",
+  "ground_truth_option_text": "nightstand, chair, table, trash bin",
+  "matches_ground_truth": false,
+  "verdict": "the spatial code's real detected order genuinely disagrees with the official ground truth's ordering -- not an engine bug, the engine correctly read the real data it had"
+ }
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/4059.json

@@ -0,0 +1,25 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 4059,
+ "question_type": "obj_appearance_order",
+ "question": "What will be the first-time appearance order of the following categories in the video: window, table, door, mirror?",
+ "options": [
+  "A. window, door, mirror, table",
+  "B. table, window, door, mirror",
+  "C. door, table, window, mirror",
+  "D. window, table, door, mirror"
+ ],
+ "full_prompt": null,
+ "answer_expected": "C",
+ "answer_given": "C",
+ "answer_raw": "C",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/4060.json

@@ -0,0 +1,38 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 4060,
+ "question_type": "obj_appearance_order",
+ "question": "What will be the first-time appearance order of the following categories in the video: nightstand, trash bin, mirror, table?",
+ "options": [
+  "A. nightstand, table, mirror, trash bin",
+  "B. trash bin, mirror, table, nightstand",
+  "C. mirror, trash bin, table, nightstand",
+  "D. nightstand, trash bin, mirror, table"
+ ],
+ "full_prompt": null,
+ "answer_expected": "A",
+ "answer_given": "D",
+ "answer_raw": "D",
+ "score": 0.0,
+ "appearance_order_diagnosis": {
+  "diagnosable": true,
+  "class_positions_in_real_order": {
+   "nightstand": 3,
+   "trash bin": 7,
+   "mirror": 8,
+   "table": 9
+  },
+  "true_order_per_spatial_code": "nightstand, trash bin, mirror, table",
+  "ground_truth_option_text": "nightstand, table, mirror, trash bin",
+  "matches_ground_truth": false,
+  "verdict": "the spatial code's real detected order genuinely disagrees with the official ground truth's ordering -- not an engine bug, the engine correctly read the real data it had"
+ }
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/4061.json

@@ -0,0 +1,38 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 4061,
+ "question_type": "obj_appearance_order",
+ "question": "What will be the first-time appearance order of the following categories in the video: trash bin, mirror, table, door?",
+ "options": [
+  "A. table, trash bin, door, mirror",
+  "B. trash bin, mirror, door, table",
+  "C. door, table, mirror, trash bin",
+  "D. trash bin, mirror, table, door"
+ ],
+ "full_prompt": null,
+ "answer_expected": "C",
+ "answer_given": "B",
+ "answer_raw": "B",
+ "score": 0.0,
+ "appearance_order_diagnosis": {
+  "diagnosable": true,
+  "class_positions_in_real_order": {
+   "trash bin": 7,
+   "mirror": 8,
+   "table": 9,
+   "door": 1
+  },
+  "true_order_per_spatial_code": "door, trash bin, mirror, table",
+  "ground_truth_option_text": "door, table, mirror, trash bin",
+  "matches_ground_truth": false,
+  "verdict": "the spatial code's real detected order genuinely disagrees with the official ground truth's ordering -- not an engine bug, the engine correctly read the real data it had"
+ }
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/4062.json

@@ -0,0 +1,25 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 4062,
+ "question_type": "obj_appearance_order",
+ "question": "What will be the first-time appearance order of the following categories in the video: table, bookshelf, chair, bed?",
+ "options": [
+  "A. bed, chair, table, bookshelf",
+  "B. table, bookshelf, chair, bed",
+  "C. table, chair, bookshelf, bed",
+  "D. chair, bookshelf, table, bed"
+ ],
+ "full_prompt": null,
+ "answer_expected": "A",
+ "answer_given": "A",
+ "answer_raw": "A",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/4063.json

@@ -0,0 +1,38 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 4063,
+ "question_type": "obj_appearance_order",
+ "question": "What will be the first-time appearance order of the following categories in the video: table, chair, trash bin, bookshelf?",
+ "options": [
+  "A. bookshelf, trash bin, chair, table",
+  "B. table, chair, trash bin, bookshelf",
+  "C. bookshelf, trash bin, table, chair",
+  "D. chair, table, bookshelf, trash bin"
+ ],
+ "full_prompt": null,
+ "answer_expected": "D",
+ "answer_given": "C",
+ "answer_raw": "C",
+ "score": 0.0,
+ "appearance_order_diagnosis": {
+  "diagnosable": true,
+  "class_positions_in_real_order": {
+   "table": 9,
+   "chair": 14,
+   "trash bin": 7,
+   "bookshelf": 12
+  },
+  "true_order_per_spatial_code": "trash bin, table, bookshelf, chair",
+  "ground_truth_option_text": "chair, table, bookshelf, trash bin",
+  "matches_ground_truth": false,
+  "verdict": "the spatial code's real detected order genuinely disagrees with the official ground truth's ordering -- not an engine bug, the engine correctly read the real data it had"
+ }
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/4064.json

@@ -0,0 +1,38 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 4064,
+ "question_type": "obj_appearance_order",
+ "question": "What will be the first-time appearance order of the following categories in the video: bed, window, table, mirror?",
+ "options": [
+  "A. bed, window, table, mirror",
+  "B. bed, table, window, mirror",
+  "C. bed, table, mirror, window",
+  "D. mirror, table, window, bed"
+ ],
+ "full_prompt": null,
+ "answer_expected": "B",
+ "answer_given": "C",
+ "answer_raw": "C",
+ "score": 0.0,
+ "appearance_order_diagnosis": {
+  "diagnosable": true,
+  "class_positions_in_real_order": {
+   "bed": 0,
+   "window": 10,
+   "table": 9,
+   "mirror": 8
+  },
+  "true_order_per_spatial_code": "bed, mirror, table, window",
+  "ground_truth_option_text": "bed, table, window, mirror",
+  "matches_ground_truth": false,
+  "verdict": "the spatial code's real detected order genuinely disagrees with the official ground truth's ordering -- not an engine bug, the engine correctly read the real data it had"
+ }
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/4065.json

@@ -0,0 +1,25 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 4065,
+ "question_type": "obj_appearance_order",
+ "question": "What will be the first-time appearance order of the following categories in the video: bookshelf, door, table, trash bin?",
+ "options": [
+  "A. bookshelf, door, table, trash bin",
+  "B. table, trash bin, bookshelf, door",
+  "C. door, table, bookshelf, trash bin",
+  "D. trash bin, table, bookshelf, door"
+ ],
+ "full_prompt": null,
+ "answer_expected": "C",
+ "answer_given": "C",
+ "answer_raw": "C",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/4066.json

@@ -0,0 +1,38 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 4066,
+ "question_type": "obj_appearance_order",
+ "question": "What will be the first-time appearance order of the following categories in the video: table, mirror, bed, trash bin?",
+ "options": [
+  "A. table, mirror, bed, trash bin",
+  "B. table, bed, trash bin, mirror",
+  "C. table, mirror, trash bin, bed",
+  "D. bed, table, mirror, trash bin"
+ ],
+ "full_prompt": null,
+ "answer_expected": "D",
+ "answer_given": "B",
+ "answer_raw": "B",
+ "score": 0.0,
+ "appearance_order_diagnosis": {
+  "diagnosable": true,
+  "class_positions_in_real_order": {
+   "table": 9,
+   "mirror": 8,
+   "bed": 0,
+   "trash bin": 7
+  },
+  "true_order_per_spatial_code": "bed, trash bin, mirror, table",
+  "ground_truth_option_text": "bed, table, mirror, trash bin",
+  "matches_ground_truth": false,
+  "verdict": "the spatial code's real detected order genuinely disagrees with the official ground truth's ordering -- not an engine bug, the engine correctly read the real data it had"
+ }
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/4067.json

@@ -0,0 +1,38 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 4067,
+ "question_type": "obj_appearance_order",
+ "question": "What will be the first-time appearance order of the following categories in the video: lamp, trash bin, chair, bookshelf?",
+ "options": [
+  "A. lamp, trash bin, chair, bookshelf",
+  "B. lamp, chair, bookshelf, trash bin",
+  "C. lamp, trash bin, bookshelf, chair",
+  "D. trash bin, chair, lamp, bookshelf"
+ ],
+ "full_prompt": null,
+ "answer_expected": "B",
+ "answer_given": "C",
+ "answer_raw": "C",
+ "score": 0.0,
+ "appearance_order_diagnosis": {
+  "diagnosable": true,
+  "class_positions_in_real_order": {
+   "lamp": 4,
+   "trash bin": 7,
+   "chair": 14,
+   "bookshelf": 12
+  },
+  "true_order_per_spatial_code": "lamp, trash bin, bookshelf, chair",
+  "ground_truth_option_text": "lamp, chair, bookshelf, trash bin",
+  "matches_ground_truth": false,
+  "verdict": "the spatial code's real detected order genuinely disagrees with the official ground truth's ordering -- not an engine bug, the engine correctly read the real data it had"
+ }
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/4068.json

@@ -0,0 +1,38 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 4068,
+ "question_type": "obj_appearance_order",
+ "question": "What will be the first-time appearance order of the following categories in the video: lamp, mirror, table, window?",
+ "options": [
+  "A. lamp, table, window, mirror",
+  "B. table, window, mirror, lamp",
+  "C. lamp, mirror, table, window",
+  "D. mirror, lamp, window, table"
+ ],
+ "full_prompt": null,
+ "answer_expected": "A",
+ "answer_given": "C",
+ "answer_raw": "C",
+ "score": 0.0,
+ "appearance_order_diagnosis": {
+  "diagnosable": true,
+  "class_positions_in_real_order": {
+   "lamp": 4,
+   "mirror": 8,
+   "table": 9,
+   "window": 10
+  },
+  "true_order_per_spatial_code": "lamp, mirror, table, window",
+  "ground_truth_option_text": "lamp, table, window, mirror",
+  "matches_ground_truth": false,
+  "verdict": "the spatial code's real detected order genuinely disagrees with the official ground truth's ordering -- not an engine bug, the engine correctly read the real data it had"
+ }
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/96/scene0580_01/4069.json

@@ -0,0 +1,38 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:96",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 96,
+ "scene": "scene0580_01",
+ "dataset": "scannet",
+ "question_id": 4069,
+ "question_type": "obj_appearance_order",
+ "question": "What will be the first-time appearance order of the following categories in the video: door, table, chair, bookshelf?",
+ "options": [
+  "A. chair, bookshelf, door, table",
+  "B. bookshelf, table, chair, door",
+  "C. door, table, chair, bookshelf",
+  "D. door, chair, table, bookshelf"
+ ],
+ "full_prompt": null,
+ "answer_expected": "D",
+ "answer_given": "C",
+ "answer_raw": "C",
+ "score": 0.0,
+ "appearance_order_diagnosis": {
+  "diagnosable": true,
+  "class_positions_in_real_order": {
+   "door": 1,
+   "table": 9,
+   "chair": 14,
+   "bookshelf": 12
+  },
+  "true_order_per_spatial_code": "door, table, bookshelf, chair",
+  "ground_truth_option_text": "door, chair, table, bookshelf",
+  "matches_ground_truth": false,
+  "verdict": "the spatial code's real detected order genuinely disagrees with the official ground truth's ordering -- not an engine bug, the engine correctly read the real data it had"
+ }
+}