initial

.gitignore

@@ -0,0 +1,2 @@
+._*
+.DS_Store

README.md

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 ---
 license: cc
+pretty_name: Neuro Evolution for eXtensible Universal Semantics Dataset
 ---
+
+# NexusDataset (Temporal Multimodal Slices)
+
+This dataset is a multi-modal, hierarchical, temporal representation derived from `HuggingFaceFV/finevideo`. It is designed for streaming training where the primary unit is a 10 ms "slice" that aggregates upward into moments (100 ms), seconds (1 s), experiences (10 s), and minutes (60 s). There are no video files in this dataset. Visual data is stored as per-frame JPEG bytes, and audio is stored as PCM16 bytes in 10 ms chunks.
+
+The Montreal Forced Aligner model was used for time-aligned orthographic transcription to both phoneme and words at the moment and second level, respectively. The original text transcription was checked for error and time-aligned at the experiences level.
+
+## Summary
+
+- Source: derived from `HuggingFaceFV/finevideo` (YouTube-origin content)
+- Modalities: audio (stereo PCM16), visual frames (JPEG bytes), text (seconds and experiences), metadata
+- Time base: all timestamps are in milliseconds
+- Primary streaming unit: 10 ms slices
+
+## Stats (current export)
+
+- Videos: 1,999
+- Duration ms (min/mean/max): 19,000 / 281,259 / 658,000
+- Total size: 541,565,728,481 bytes (approx 541.6 GB)
+
+Row counts:
+- slices: 57,246,000
+- moments: 5,724,600
+- seconds: 572,460
+- experiences: 57,246
+- minutes: 10,317
+- frames: 15,781,125
+- meta: 1,999
+
+## Dataset structure
+
+All data is stored in Parquet shards:
+
+```
+slices-00000-of-000NN.parquet
+moments-00000-of-000NN.parquet
+seconds-00000-of-000NN.parquet
+experiences-00000-of-000NN.parquet
+minutes-00000-of-000NN.parquet
+frames-00000-of-000NN.parquet
+meta-00000-of-000NN.parquet
+```
+
+Each table uses `video_id` as the primary key to connect across tables. Index columns are 0-based within each video (e.g., `slice_idx`, `moment_idx`, `frame_idx`).
+
+### slices (10 ms)
+
+Core streaming unit. Use this table for training.
+
+Key fields:
+- `video_id`, `slice_idx`, `start_ms`
+- `audio_l_pcm16`, `audio_r_pcm16`: 320-byte PCM16 chunks (16 kHz, 10 ms)
+- `frame_idx`: points to `frames.frame_idx` for the same `video_id`
+- `moment_idx`, `second_idx`, `experience_idx`, `minute_idx`
+- `is_video_start`, `is_video_end`
+- Optional sensors: `imu`, `gps`, `temp`, `humidity`, `baro`, `lidar`, `ranges`, `screen`, `data`
+
+### moments (100 ms)
+
+- `video_id`, `moment_idx`, `start_ms`, `end_ms`
+- `slice_start_idx`, `slice_end_idx`
+- `phoneme` (nullable)
+
+### seconds (1 s)
+
+- `video_id`, `second_idx`, `start_ms`, `end_ms`
+- `moment_start_idx`, `moment_end_idx`
+- `words`: list of word tokens aligned to the second
+
+### experiences (10 s)
+
+- `video_id`, `experience_idx`, `start_ms`, `end_ms`
+- `second_start_idx`, `second_end_idx`
+- `statements`: list of text segments for the 10 s window
+- `gestures`: list of gesture tokens (nullable)
+
+### minutes (60 s)
+
+- `video_id`, `minute_idx`, `start_ms`, `end_ms`
+- `experience_start_idx`, `experience_end_idx`
+- `actions`: list of action tokens (nullable)
+
+### frames
+
+- `video_id`, `frame_idx`, `frame_time_ms`
+- `image`: struct with `{bytes, path}` where `bytes` are JPEG bytes and `path` is null
+
+### meta
+
+Top-level metadata from the source dataset. Stored as strings if not scalar.
+
+Key fields:
+- `video_id`, `duration_ms`, `resolution`
+- Content metadata: `content_parent_category`, `content_fine_category`, `content_metadata`
+- YouTube metadata: `youtube_title`, `youtube_description`, `youtube_channel`, `youtube_categories`, `youtube_tags`, `youtube_upload_date`, etc.
+
+## Streaming usage
+
+Slices are ordered by `(video_id, slice_idx)` in each shard, so you can stream them in order. Use `is_video_start` / `is_video_end` or `video_id` changes to detect boundaries.
+
+Example (local or after cloning the dataset repo):
+
+```python
+from datasets import load_dataset
+
+data_files = "slices-*.parquet"
+ds = load_dataset("parquet", data_files=data_files, split="train", streaming=True)
+
+# Stream the first 10 minutes of slices
+total_ms = 0
+for row in ds:
+    total_ms = row["start_ms"]
+    if total_ms >= 10 * 60 * 1000:
+        break
+```
+
+## Decoding examples
+
+Decode audio:
+
+```python
+import numpy as np
+
+pcm = row["audio_l_pcm16"]  # bytes
+samples = np.frombuffer(pcm, dtype="<i2")  # int16
+```
+
+Decode frames as images:
+
+```python
+from datasets import load_dataset, Image
+
+frames = load_dataset("parquet", data_files="frames-*.parquet", split="train")
+frames = frames.cast_column("image", Image())
+```
+
+## Intended use
+
+- Streaming temporal modeling
+- Multimodal alignment research
+- Hierarchical sequence modeling
+
+## Limitations
+
+- Derived from YouTube content; metadata and transcription quality depend on the source dataset and `Montreal Forced Aligner`
+- Audio and frames are stored independently; use `video_id` and indices to align.
+
+## License and attribution
+
+This dataset is derived from `HuggingFaceFV/finevideo`. Please follow the original dataset license and YouTube content terms when using or redistributing this dataset.

dataset_report.json

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+        }
+      ],
+      "schema_mismatch": false,
+      "shard_sample": [
+        "/Volumes/Data/NexusDataset/moments-00000-of-00106.parquet",
+        "/Volumes/Data/NexusDataset/moments-00001-of-00106.parquet",
+        "/Volumes/Data/NexusDataset/moments-00002-of-00106.parquet",
+        "/Volumes/Data/NexusDataset/moments-00003-of-00106.parquet",
+        "/Volumes/Data/NexusDataset/moments-00004-of-00106.parquet"
+      ],
+      "shards": 106,
+      "total_bytes": 106752880
+    },
+    "seconds": {
+      "rows": 572460,
+      "sample_row": {
+        "end_ms": 1000,
+        "moment_end_idx": 9,
+        "moment_start_idx": 0,
+        "second_idx": 0,
+        "start_ms": 0,
+        "video_id": "-0jcDYcjAuI",
+        "words": []
+      },
+      "schema": "video_id: string\nsecond_idx: int32\nstart_ms: int64\nend_ms: int64\nmoment_start_idx: int32\nmoment_end_idx: int32\nwords: list<element: string>\n  child 0, element: string",
+      "schema_fields": [
+        {
+          "name": "video_id",
+          "nullable": true,
+          "type": "string"
+        },
+        {
+          "name": "second_idx",
+          "nullable": true,
+          "type": "int32"
+        },
+        {
+          "name": "start_ms",
+          "nullable": true,
+          "type": "int64"
+        },
+        {
+          "name": "end_ms",
+          "nullable": true,
+          "type": "int64"
+        },
+        {
+          "name": "moment_start_idx",
+          "nullable": true,
+          "type": "int32"
+        },
+        {
+          "name": "moment_end_idx",
+          "nullable": true,
+          "type": "int32"
+        },
+        {
+          "name": "words",
+          "nullable": true,
+          "type": "list<element: string>"
+        }
+      ],
+      "schema_mismatch": false,
+      "shard_sample": [
+        "/Volumes/Data/NexusDataset/seconds-00000-of-00106.parquet",
+        "/Volumes/Data/NexusDataset/seconds-00001-of-00106.parquet",
+        "/Volumes/Data/NexusDataset/seconds-00002-of-00106.parquet",
+        "/Volumes/Data/NexusDataset/seconds-00003-of-00106.parquet",
+        "/Volumes/Data/NexusDataset/seconds-00004-of-00106.parquet"
+      ],
+      "shards": 106,
+      "total_bytes": 16658651
+    },
+    "slices": {
+      "rows": 57246000,
+      "sample_row": {
+        "audio_l_pcm16": {
+          "__bytes__": 320,
+          "head_hex": "000000000000000000000000"
+        },
+        "audio_r_pcm16": {
+          "__bytes__": 320,
+          "head_hex": "000000000000000000000000"
+        },
+        "baro": null,
+        "data": null,
+        "experience_idx": 0,
+        "frame_idx": 0,
+        "gps": null,
+        "humidity": null,
+        "imu": null,
+        "is_video_end": false,
+        "is_video_start": true,
+        "lidar": null,
+        "minute_idx": 0,
+        "moment_idx": 0,
+        "ranges": null,
+        "screen": null,
+        "second_idx": 0,
+        "slice_idx": 0,
+        "start_ms": 0,
+        "temp": null,
+        "text": null,
+        "video_id": "-0jcDYcjAuI"
+      },
+      "schema": "video_id: string\nslice_idx: int32\nstart_ms: int64\naudio_l_pcm16: fixed_size_binary[320]\naudio_r_pcm16: fixed_size_binary[320]\nframe_idx: int64\nmoment_idx: int32\nsecond_idx: int32\nexperience_idx: int32\nminute_idx: int32\ntext: string\nimu: list<element: list<element: float>>\n  child 0, element: list<element: float>\n      child 0, element: float\ngps: list<element: double>\n  child 0, element: double\ntemp: float\nhumidity: float\nbaro: float\nlidar: string\nranges: list<element: float>\n  child 0, element: float\nscreen: string\ndata: string\nis_video_start: bool\nis_video_end: bool",
+      "schema_fields": [
+        {
+          "name": "video_id",
+          "nullable": true,
+          "type": "string"
+        },
+        {
+          "name": "slice_idx",
+          "nullable": true,
+          "type": "int32"
+        },
+        {
+          "name": "start_ms",
+          "nullable": true,
+          "type": "int64"
+        },
+        {
+          "name": "audio_l_pcm16",
+          "nullable": true,
+          "type": "fixed_size_binary[320]"
+        },
+        {
+          "name": "audio_r_pcm16",
+          "nullable": true,
+          "type": "fixed_size_binary[320]"
+        },
+        {
+          "name": "frame_idx",
+          "nullable": true,
+          "type": "int64"
+        },
+        {
+          "name": "moment_idx",
+          "nullable": true,
+          "type": "int32"
+        },
+        {
+          "name": "second_idx",
+          "nullable": true,
+          "type": "int32"
+        },
+        {
+          "name": "experience_idx",
+          "nullable": true,
+          "type": "int32"
+        },
+        {
+          "name": "minute_idx",
+          "nullable": true,
+          "type": "int32"
+        },
+        {
+          "name": "text",
+          "nullable": true,
+          "type": "string"
+        },
+        {
+          "name": "imu",
+          "nullable": true,
+          "type": "list<element: list<element: float>>"
+        },
+        {
+          "name": "gps",
+          "nullable": true,
+          "type": "list<element: double>"
+        },
+        {
+          "name": "temp",
+          "nullable": true,
+          "type": "float"
+        },
+        {
+          "name": "humidity",
+          "nullable": true,
+          "type": "float"
+        },
+        {
+          "name": "baro",
+          "nullable": true,
+          "type": "float"
+        },
+        {
+          "name": "lidar",
+          "nullable": true,
+          "type": "string"
+        },
+        {
+          "name": "ranges",
+          "nullable": true,
+          "type": "list<element: float>"
+        },
+        {
+          "name": "screen",
+          "nullable": true,
+          "type": "string"
+        },
+        {
+          "name": "data",
+          "nullable": true,
+          "type": "string"
+        },
+        {
+          "name": "is_video_start",
+          "nullable": true,
+          "type": "bool"
+        },
+        {
+          "name": "is_video_end",
+          "nullable": true,
+          "type": "bool"
+        }
+      ],
+      "schema_mismatch": false,
+      "shard_sample": [
+        "/Volumes/Data/NexusDataset/slices-00000-of-00106.parquet",
+        "/Volumes/Data/NexusDataset/slices-00001-of-00106.parquet",
+        "/Volumes/Data/NexusDataset/slices-00002-of-00106.parquet",
+        "/Volumes/Data/NexusDataset/slices-00003-of-00106.parquet",
+        "/Volumes/Data/NexusDataset/slices-00004-of-00106.parquet"
+      ],
+      "shards": 106,
+      "total_bytes": 31709322100
+    }
+  },
+  "tmp_shard_count": 0,
+  "tmp_shards": []
+}

dataset_report.md

@@ -0,0 +1,295 @@
+# Dataset Report
+
+- Root: `/Volumes/Data/NexusDataset`
+- Generated: `2025-12-28T05:30:25.793569+00:00`
+- Finalized: `True`
+- Processed videos: `1999`
+- Pending videos: `0`
+- Temp shards: `0`
+- Video count: `1999`
+- Duration ms (min/mean/max): `19000` / `281259` / `658000`
+
+## Tables
+
+### slices
+
+- Shards: `106`
+- Rows: `57246000`
+- Size bytes: `31709322100`
+- Schema mismatch: `False`
+
+**Schema Fields**
+
+- `video_id`: `string` (nullable=True)
+- `slice_idx`: `int32` (nullable=True)
+- `start_ms`: `int64` (nullable=True)
+- `audio_l_pcm16`: `fixed_size_binary[320]` (nullable=True)
+- `audio_r_pcm16`: `fixed_size_binary[320]` (nullable=True)
+- `frame_idx`: `int64` (nullable=True)
+- `moment_idx`: `int32` (nullable=True)
+- `second_idx`: `int32` (nullable=True)
+- `experience_idx`: `int32` (nullable=True)
+- `minute_idx`: `int32` (nullable=True)
+- `text`: `string` (nullable=True)
+- `imu`: `list<element: list<element: float>>` (nullable=True)
+- `gps`: `list<element: double>` (nullable=True)
+- `temp`: `float` (nullable=True)
+- `humidity`: `float` (nullable=True)
+- `baro`: `float` (nullable=True)
+- `lidar`: `string` (nullable=True)
+- `ranges`: `list<element: float>` (nullable=True)
+- `screen`: `string` (nullable=True)
+- `data`: `string` (nullable=True)
+- `is_video_start`: `bool` (nullable=True)
+- `is_video_end`: `bool` (nullable=True)
+
+**Sample Row**
+
+```json
+{
+  "video_id": "-0jcDYcjAuI",
+  "slice_idx": 0,
+  "start_ms": 0,
+  "audio_l_pcm16": {
+    "__bytes__": 320,
+    "head_hex": "000000000000000000000000"
+  },
+  "audio_r_pcm16": {
+    "__bytes__": 320,
+    "head_hex": "000000000000000000000000"
+  },
+  "frame_idx": 0,
+  "moment_idx": 0,
+  "second_idx": 0,
+  "experience_idx": 0,
+  "minute_idx": 0,
+  "text": null,
+  "imu": null,
+  "gps": null,
+  "temp": null,
+  "humidity": null,
+  "baro": null,
+  "lidar": null,
+  "ranges": null,
+  "screen": null,
+  "data": null,
+  "is_video_start": true,
+  "is_video_end": false
+}
+```
+
+### moments
+
+- Shards: `106`
+- Rows: `5724600`
+- Size bytes: `106752880`
+- Schema mismatch: `False`
+
+**Schema Fields**
+
+- `video_id`: `string` (nullable=True)
+- `moment_idx`: `int32` (nullable=True)
+- `start_ms`: `int64` (nullable=True)
+- `end_ms`: `int64` (nullable=True)
+- `slice_start_idx`: `int32` (nullable=True)
+- `slice_end_idx`: `int32` (nullable=True)
+- `phoneme`: `string` (nullable=True)
+
+**Sample Row**
+
+```json
+{
+  "video_id": "-0jcDYcjAuI",
+  "moment_idx": 0,
+  "start_ms": 0,
+  "end_ms": 100,
+  "slice_start_idx": 0,
+  "slice_end_idx": 9,
+  "phoneme": null
+}
+```
+
+### seconds
+
+- Shards: `106`
+- Rows: `572460`
+- Size bytes: `16658651`
+- Schema mismatch: `False`
+
+**Schema Fields**
+
+- `video_id`: `string` (nullable=True)
+- `second_idx`: `int32` (nullable=True)
+- `start_ms`: `int64` (nullable=True)
+- `end_ms`: `int64` (nullable=True)
+- `moment_start_idx`: `int32` (nullable=True)
+- `moment_end_idx`: `int32` (nullable=True)
+- `words`: `list<element: string>` (nullable=True)
+
+**Sample Row**
+
+```json
+{
+  "video_id": "-0jcDYcjAuI",
+  "second_idx": 0,
+  "start_ms": 0,
+  "end_ms": 1000,
+  "moment_start_idx": 0,
+  "moment_end_idx": 9,
+  "words": []
+}
+```
+
+### experiences
+
+- Shards: `106`
+- Rows: `57246`
+- Size bytes: `8470527`
+- Schema mismatch: `False`
+
+**Schema Fields**
+
+- `video_id`: `string` (nullable=True)
+- `experience_idx`: `int32` (nullable=True)
+- `start_ms`: `int64` (nullable=True)
+- `end_ms`: `int64` (nullable=True)
+- `second_start_idx`: `int32` (nullable=True)
+- `second_end_idx`: `int32` (nullable=True)
+- `statements`: `list<element: string>` (nullable=True)
+- `gestures`: `list<element: string>` (nullable=True)
+
+**Sample Row**
+
+```json
+{
+  "video_id": "-0jcDYcjAuI",
+  "experience_idx": 0,
+  "start_ms": 0,
+  "end_ms": 10000,
+  "second_start_idx": 0,
+  "second_end_idx": 9,
+  "statements": [
+    " The pre-flare maneuver executed."
+  ],
+  "gestures": []
+}
+```
+
+### minutes
+
+- Shards: `106`
+- Rows: `10317`
+- Size bytes: `3108903`
+- Schema mismatch: `False`
+
+**Schema Fields**
+
+- `video_id`: `string` (nullable=True)
+- `minute_idx`: `int32` (nullable=True)
+- `start_ms`: `int64` (nullable=True)
+- `end_ms`: `int64` (nullable=True)
+- `experience_start_idx`: `int32` (nullable=True)
+- `experience_end_idx`: `int32` (nullable=True)
+- `actions`: `list<element: string>` (nullable=True)
+
+**Sample Row**
+
+```json
+{
+  "video_id": "-0jcDYcjAuI",
+  "minute_idx": 0,
+  "start_ms": 0,
+  "end_ms": 60000,
+  "experience_start_idx": 0,
+  "experience_end_idx": 5,
+  "actions": []
+}
+```
+
+### frames
+
+- Shards: `106`
+- Rows: `15781125`
+- Size bytes: `509695327843`
+- Schema mismatch: `False`
+
+**Schema Fields**
+
+- `video_id`: `string` (nullable=True)
+- `frame_idx`: `int64` (nullable=True)
+- `frame_time_ms`: `int64` (nullable=True)
+- `image`: `struct<bytes: binary, path: string>` (nullable=True)
+
+**Sample Row**
+
+```json
+{
+  "video_id": "-0jcDYcjAuI",
+  "frame_idx": 0,
+  "frame_time_ms": 0,
+  "image": {
+    "bytes": {
+      "__bytes__": 1600,
+      "head_hex": "ffd8ffe000104a4649460001"
+    },
+    "path": null
+  }
+}
+```
+
+### meta
+
+- Shards: `106`
+- Rows: `1999`
+- Size bytes: `26087577`
+- Schema mismatch: `False`
+
+**Schema Fields**
+
+- `video_id`: `string` (nullable=True)
+- `duration_ms`: `int64` (nullable=True)
+- `content_fine_category`: `string` (nullable=True)
+- `content_metadata`: `string` (nullable=True)
+- `content_parent_category`: `string` (nullable=True)
+- `original_json_filename`: `string` (nullable=True)
+- `original_video_filename`: `string` (nullable=True)
+- `resolution`: `string` (nullable=True)
+- `text_to_speech_word_count`: `string` (nullable=True)
+- `youtube_age_limit`: `string` (nullable=True)
+- `youtube_categories`: `string` (nullable=True)
+- `youtube_channel`: `string` (nullable=True)
+- `youtube_channel_follower_count`: `string` (nullable=True)
+- `youtube_comment_count`: `string` (nullable=True)
+- `youtube_description`: `string` (nullable=True)
+- `youtube_like_count`: `string` (nullable=True)
+- `youtube_tags`: `string` (nullable=True)
+- `youtube_title`: `string` (nullable=True)
+- `youtube_upload_date`: `string` (nullable=True)
+- `youtube_view_count`: `string` (nullable=True)
+
+**Sample Row**
+
+```json
+{
+  "video_id": "-0jcDYcjAuI",
+  "duration_ms": 154000,
+  "content_fine_category": "Space Missions",
+  "content_metadata": "{\"characterList\": [{\"characterId\": \"1\", \"description\": \"We only hear the voice of the pilot who is controlling the space shuttle. We cannot see him.\", \"name\": \"Pilot\"}, {\"characterId\": \"2\", \"description\": \"We only hear the voice of the tower operator, who is coordinating the landing. We cannot see him.\", \"name\": \"Tower Operator\"}], \"description\": \"A detailed analysis of the landing sequence of Space Shuttle Atlantis, including character details, scene breakdown, thematic elements, and trimming suggestions.\", \"fps\": 29.97, \"qAndA\": [{\"answer\": \"The pilot executes a pre-flare maneuver, a slight upward adjustment to the shuttle's trajectory just before touching down.\", \"question\": \"What maneuver does the pilot execute just before landing?\"}, {\"answer\": \"The space shuttle uses a drag chute to assist with deceleration upon landing.\", \"question\": \"What method does the space shuttle use to slow down on the runway?\"}, {\"answer\": \"The transition to black and white evokes a sense of nostalgia and a bittersweet feeling of finality, reflecting the end of an era.\", \"question\": \"What emotional tone does the transition to black and white imagery convey?\"}, {\"answer\": \"The pilot emphasizes that the spirit of exploration will continue, despite the conclusion of the space shuttle program. He implies that America's journey in space is far from over.\", \"question\": \"What message does the pilot convey in his final statement?\"}, {\"answer\": \"The pilot's tribute to Columbia, Challenger, Discovery, and Endeavour acknowledges the sacrifices made in the pursuit of space exploration and honors the legacy of the entire program. It also underscores the collective effort and shared history that have shaped America's spacefaring identity.\", \"question\": \"What symbolic meaning can be attributed to the pilot's tribute to the previous space shuttles?\"}], \"scenes\": [{\"activities\": [{\"description\": \"Space shuttle landing\", \"timestamp\": {\"end_timestamp\": \"00:02:33.987\", \"start_timestamp\": \"00:00:00.000\"}}, {\"description\": \"Deploying drag chute\", \"timestamp\": {\"end_timestamp\": \"00:00:29.997\", \"start_timestamp\": \"00:00:29.997\"}}, {\"description\": \"Lowering nose gear\", \"timestamp\": {\"end_timestamp\": \"00:00:35.002\", \"start_timestamp\": \"00:00:35.002\"}}, {\"description\": \"Engaging brakes\", \"timestamp\": {\"end_timestamp\": \"00:00:41.008\", \"start_timestamp\": \"00:00:41.008\"}}, {\"description\": \"Crew communication with tower\", \"timestamp\": {\"end_timestamp\": \"00:02:33.987\", \"start_timestamp\": \"00:01:25.986\"}}], \"audioVisualCorrelation\": 0.7, \"cast\": [\"Pilot\", \"Tower Operator\"], \"characterInteraction\": [{\"characters\": [\"Pilot\", \"Tower Operator\"], \"description\": \"The pilot and the tower operator engage in a heartfelt conversation, reflecting on the legacy of the space shuttle program and expressing their emotions.\"}], \"contextualRelevance\": \"The shift to black and white visuals symbolizes the end of an era, suggesting nostalgia and a sense of loss. The pilot's statement 'America is not going to stop exploring' signifies the ongoing spirit of human curiosity and the pursuit of knowledge.\", \"dynamismScore\": 0.6, \"mood\": {\"description\": \"Proud\", \"keyMoments\": [{\"changeDescription\": \"Transition from color to black and white signifies a shift to reflection and nostalgia.\", \"timestamp\": \"00:02:05.993\"}]}, \"narrativeProgression\": [{\"description\": \"The scene begins with the space shuttle making its final approach for landing.\", \"timestamp\": \"00:00:00.000\"}, {\"description\": \"The crew communicates with the tower, confirming a successful landing.\", \"timestamp\": \"00:01:25.986\"}, {\"description\": \"The tower operator congratulates the crew and acknowledges the historical significance of the event.\", \"timestamp\": \"00:01:34.995\"}, {\"description\": \"The pilot pays tribute to all the space shuttles and thanks them for their service.\", \"timestamp\": \"00:02:13.000\"}, {\"description\": \"The tower operator expresses similar sentiments and highlights the continued spirit of exploration in America.\", \"timestamp\": \"00:02:25.012\"}], \"props\": [{\"name\": \"Space Shuttle Atlantis\", \"timestamp\": {\"end_timestamp\": \"00:02:33.987\", \"start_timestamp\": \"00:00:00.000\"}}, {\"name\": \"Drag chute\", \"timestamp\": {\"end_timestamp\": \"00:00:40.007\", \"start_timestamp\": \"00:00:29.997\"}}, {\"name\": \"Runway\", \"timestamp\": {\"end_timestamp\": \"00:02:33.987\", \"start_timestamp\": \"00:00:16.016\"}}], \"sceneId\": 1, \"thematicElements\": \"The scene celebrates the achievements of the space shuttle program and its impact on the human understanding of the universe. It also emphasizes the dedication and hard work of countless individuals who made this endeavor possible.\", \"timestamps\": {\"end_timestamp\": \"00:02:34.054\", \"start_timestamp\": \"00:00:00.000\"}, \"title\": \"Landing of Space Shuttle Atlantis\", \"videoEditingDetails\": [{\"description\": \"Transition: Fade to black\", \"timestamps\": {\"end_timestamp\": \"00:00:09.009\", \"start_timestamp\": \"00:00:08.008\"}}, {\"description\": \"Transition: Fade in\", \"timestamps\": {\"end_timestamp\": \"00:00:10.010\", \"start_timestamp\": \"00:00:09.009\"}}, {\"description\": \"Transition: Cut to black and white\", \"timestamps\": {\"end_timestamp\": \"00:02:05.993\", \"start_timestamp\": \"00:02:05.993\"}}]}], \"storylines\": {\"climax\": {\"description\": \"Touchdown and confirmation of successful landing\", \"timestamp\": \"00:01:25.986\"}, \"description\": \"Final Landing of Space Shuttle Atlantis\", \"scenes\": [1]}, \"title\": \"Space Shuttle Atlantis Landing Analysis\", \"trimmingSuggestions\": [{\"description\": \"The scene could be made more dynamic by trimming the extended dialogue at the end. While the sentiments expressed are meaningful, they could be condensed to maintain audience engagement.\", \"timestamps\": {\"end_timestamp\": \"00:02:33.987\", \"start_timestamp\": \"00:01:59.987\"}}]}",
+  "content_parent_category": "Science & Technology",
+  "original_json_filename": "-0jcDYcjAuI.json",
+  "original_video_filename": "-0jcDYcjAuI.mp4",
+  "resolution": "640x360",
+  "text_to_speech_word_count": "217",
+  "youtube_age_limit": "0",
+  "youtube_categories": "[\"Science & Technology\"]",
+  "youtube_channel": "Creative Commons Collection",
+  "youtube_channel_follower_count": "13",
+  "youtube_comment_count": "0",
+  "youtube_description": "Atlantis lands at NASA's Kennedy Space Center before dawn on July 21, 2011, wrapping up the mission of the space shuttle program.",
+  "youtube_like_count": "0",
+  "youtube_tags": "[\"Space Shuttle Atlantis (Spacecraft)\", \"Astronomy (Field Of Study)\"]",
+  "youtube_title": "Atlantis Lands, Completing Final Shuttle Mission",
+  "youtube_upload_date": "20150324",
+  "youtube_view_count": "4"
+}
+```

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