Error code:   JWTInvalidSignature
Exception:    InvalidSignatureError
Message:      Signature verification failed
Traceback:    Traceback (most recent call last):
                File "/src/libs/libapi/src/libapi/jwt_token.py", line 286, in validate_jwt
                  decoded = jwt.decode(
                      jwt=token,
                  ...<2 lines>...
                      options=options,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 368, in decode
                  decoded = self.decode_complete(
                      jwt,
                  ...<8 lines>...
                      leeway=leeway,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 265, in decode_complete
                  decoded = self._jws.decode_complete(
                      jwt,
                  ...<3 lines>...
                      detached_payload=detached_payload,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 270, in decode_complete
                  self._verify_signature(
                  ~~~~~~~~~~~~~~~~~~~~~~^
                      signing_input,
                      ^^^^^^^^^^^^^^
                  ...<4 lines>...
                      options=merged_options,
                      ^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 417, in _verify_signature
                  raise InvalidSignatureError("Signature verification failed")
              jwt.exceptions.InvalidSignatureError: Signature verification failed

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Dataset Card for Beverage Energy Tracker

This dataset card documents the Beverage Energy Tracker dataset.
It contains nutritional and energy-related features of 30 unique beverages, with an augmented split expanding to 300 rows.

Dataset Details

Dataset Description

Curated by: Bareethul Kader (Carnegie Mellon University, EST&P program)
Language(s): English (column labels, beverage names)
License: CC BY 4.0
Repository: bareethul/beverage-energy-tracker

Uses

Direct Use

Educational practice in data collection, preprocessing, and augmentation.
Demonstration of label-preserving jitter augmentation for tabular datasets.
Binary classification task: predict whether a beverage is high sugar or not.

Out-of-Scope Use

Not intended for clinical, nutritional, or health policy decision-making.
Values are approximate and curated manually - not to be used for dietary guidance.

Dataset Structure

Original split: 30 manually curated beverages.
Augmented split: 300 rows, generated with Gaussian jitter (for continuous features) and ±1 step encoding (for ordinal features).

Features:

Beverage type (string)
Added sugar (g) (float)
Calories (float)
Volume (mL) (integer)
Energy rating (1–5) (ordinal)
is_high_sugar (binary target: 1 = sugar ≥ 20g, 0 = sugar < 20g)

Dataset Creation

Curation Rationale
To study how nutritional features (sugar, calories, volume) can relate to sugar content classification (high vs low).

Data Collection and Processing

Data manually collected from: Starbucks, ALDI USA, MarketDistrict, Amazon, Walmart product pages.
Manual preprocessing and type formatting were applied (e.g., ensuring numeric columns, clipping noise to avoid negative values).
Binary target is_high_sugar was derived using a threshold of 20g sugar.

Source Data Producers

Original producers: beverage manufacturers and retailers (nutritional info posted publicly).
Dataset curated by Bareethul Kader for educational purposes.

Annotations

Annotation Process: Binary target derived from numeric sugar values.
Annotators: Dataset creator.

Personal and Sensitive Information

No personal or sensitive data included.

Bias, Risks, and Limitations

Limited to 30 beverages (not representative of all products).
Energy rating and is_high_sugar are simplified labels, not standardized nutrition metrics.
Augmentation may create unrealistic numeric combinations.

Recommendations

Users should be aware of the risks, biases, and limitations of the dataset.
It is intended only for educational demonstrations of dataset creation, preprocessing, and augmentation.
Do not generalize results to real nutrition/health applications.

Citation

BibTeX:

@dataset{bareethul_beverage_energy_tracker,
  author       = {Kader, Bareethul},
  title        = {Beverage Energy Tracker},
  year         = {2025},
  publisher    = {Hugging Face Datasets},
  url          = {https://huggingface.co/datasets/bareethul/beverage-energy-tracker}
}

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