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Hao13911949273/MinusData-Chem-Negative-PoC

published by @Hao13911949273

Alignment dataset tracked in the /datasets sub-catalog.

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Created on HF
2026-10-12
Age
9 days ago

Description

MinusData: Chemistry Negative Samples (Synthetic PoC)

A schema and QC pipeline for standardizing negative (failed) reaction records into

model-ready tabular data. This PoC release contains synthetic examples only and is

intended for pipeline integration testing, not for training or benchmarking real models.

Version 1.2. Filename note: HuggingFace expects this file to be named README.md at the repo root.

1. Data source and synthetic declaration

Status: all 30… See the full description on the dataset page: https://huggingface.co/datasets/Hao13911949273/MinusData-Chem-Negative-PoC.

Tags

task_categories:tabular-classificationtask_categories:reinforcement-learninglanguage:enlicense:cc-by-4.0size_categories:n<1Kformat:parquetmodality:tabularmodality:textlibrary:datasetslibrary:pandaslibrary:polarslibrary:mlcroissantregion:uschemistrynegative-samplingfailed-reactionssynthetic-dataai4sminusdata

README current version from Hugging Face


license: cc-by-4.0
language:

  • en
    pretty_name: "MinusData Chemistry Negative Samples (Synthetic PoC)"
    size_categories:
  • n<1K
    task_categories:
  • tabular-classification
  • reinforcement-learning
    tags:
  • chemistry
  • negative-sampling
  • failed-reactions
  • synthetic-data
  • ai4s
  • minusdata
    configs:
  • config_name: default
    data_files: MinusData_Chem_Negative_PoC.parquet

MinusData: Chemistry Negative Samples (Synthetic PoC)

A schema and QC pipeline for standardizing negative (failed) reaction records into
model-ready tabular data. This PoC release contains synthetic examples only and is
intended for pipeline integration testing, not for training or benchmarking real models.

Version 1.2. Filename note: HuggingFace expects this file to be named README.md at the repo root.

1. Data source and synthetic declaration

  • Status: all 30 records are synthetic (data_source_type = synthetic_mock_example,
    Parquet metadata key minusdata_synthetic = true).
  • Conditions and outcomes are illustrative and were not experimentally verified. Yields are assigned, not measured.
  • Purpose: PoC integration, testing of data loaders, and exercising RL reward/penalty plumbing.

2. Success / failure definition

  • Successful: assigned yield ≥ 0.05 (is_successful = true). This includes exactly 0.05 (one boundary case is included).
  • Failure (negative sample): assigned yield < 0.05.
  • The 5% threshold is a configurable convention, not a chemical constant. Re-label for your own task if needed.

3. Penalty score (heuristic)

penalty_score is 0.0 for successful reactions. For failures it is looked up by failure_category.
These weights are human-designed heuristics, not experimentally calibrated; re-tune them for your own objective.
Rules are shipped machine-readably in penalty_config.json.

failure_category penalty_score allowed yield range design rationale
catalyst_decomposition 1.0 0.0 – 0.049 Most severe: the catalyst itself is destroyed (e.g. Pd black, Cu disproportionation), so the route cannot proceed at all.
thermal_instability 0.9 0.0 – 0.049 High severity: substrate, reagent or intermediate degrades under the chosen temperature.
no_conversion 0.8 0.0 – 0.0 Moderate-to-high severity: starting materials recovered unchanged; conditions are inert for this transformation.
byproduct_dominant 0.7 0.001 – 0.049 Lower severity: trace target formed, but competing side reactions dominate; the route is closer to viable.

4. Contents

30 records: 6 successful, 24 failed.

category count
none (successful) 6
catalyst_decomposition 6
thermal_instability 6
no_conversion 6
byproduct_dominant 6

Files: MinusData_Chem_Negative_PoC.parquet, penalty_config.json, MinusData_Rejected_Log.csv, build_minusdata_poc.py.

5. Schema

column type description
minusdata_id string Stable content hash ID (SHA-1 of reaction type + SMILES + conditions, 16 hex chars).
data_source_type string Origin of the record. All rows in this release: synthetic_mock_example.
source_ref string Generator reference for the synthetic record.
reaction_smiles string Intended transformation reactants>>intended product. By-products and reagents are omitted.
reaction_type string Reaction class label.
solvent string Solvent. Null = not recorded.
catalyst string Catalyst/promoter. none = explicitly none used; null = not recorded.
base string Base. none = explicitly none used; null = not recorded.
temperature_celsius double Reaction temperature in °C.
time_hours double Reaction time in hours.
is_successful bool True if product_yield >= success threshold.
product_yield double Assigned yield as a fraction in [0, 1] (synthetic, not measured).
penalty_score double 0.0 for successes; failures use the lookup table in this card.
failure_category string Enumerated failure class; none for successes.
failure_description string Free-text description; none for successes.
qc_smiles_validated bool True if every SMILES component was parsed by RDKit.
qc_atom_check_passed bool True if the element-wise atom availability check passed (see QC section).
notes string Generation notes (e.g. threshold boundary case). Nullable.

6. Quality control

Each raw record passes these checks; failures are written to MinusData_Rejected_Log.csv with a reason (nothing is dropped silently):

  1. product_yield must be in [0, 1] (catches percentages).
  2. All SMILES components must parse in RDKit (version recorded in file metadata: 2026.09.1).
  3. Element-wise atom availability check: for every element (including H), the intended product may not contain more atoms than the reactants supply. By-products and reagents are omitted from reaction_smiles, so this is not a full stoichiometric balance, and it does not verify chemistry correctness or mechanism.
  4. Failure category must be a known enum value, consistent with the yield range, and absent for successes.
  5. Duplicates (same reaction type, SMILES and conditions) are rejected via the content-hash ID.

The release build also includes 6 deliberately flawed test records, all of which are expected to appear in the rejected log.

7. Loading

import pandas as pd
df = pd.read_parquet("MinusData_Chem_Negative_PoC.parquet")

# or
from datasets import load_dataset
ds = load_dataset("parquet", data_files="MinusData_Chem_Negative_PoC.parquet")

8. Intended and out-of-scope use

  • Intended: testing ingestion pipelines, schema compatibility, penalty-term wiring in RL setups, demonstrating the format.
  • Out of scope: training or evaluating production reaction-prediction models; any claim about real-world failure distributions or false-positive reduction. No such effect has been measured with this data.

9. Limitations

  • Synthetic and tiny (30 rows); does not reflect real experimental failure distributions.
  • Reaction classes are simple textbook examples; conditions are plausible but unverified.
  • reaction_smiles encodes the intended reaction; failed runs did not necessarily give that product.
  • Penalty weights are arbitrary heuristics.

10. License

This synthetic sample is released under CC-BY-4.0. This applies only to this synthetic release.
Any future real-world data would be licensed according to its source and the data providers' authorization.

11. Citation and contact

Please cite as: MinusData Chemistry Negative Samples (Synthetic PoC), v1.2.
Contact: [to be filled in]

README history 10 revisions

Every night we snapshot the README of every dataset in the catalog. When the SHA changes we archive the new version and diff it against the last. This is the evolving thought record of the alignment-data field: what the author decided to say about the corpus, and how that framing shifted over time.

  1. 2026-10-12Upload build_minusdata_poc.py with huggingface_hub728a2ed6.6 KB
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  2. 2026-10-12Upload make_sample_eln.py with huggingface_hub8880ed26.6 KB
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  3. 2026-10-12Upload test_ingest.py with huggingface_hub55972d26.6 KB
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  4. 2026-10-12Upload penalty_config.json with huggingface_hub4bce7b36.6 KB
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  5. 2026-10-12Upload minusdata_ingest.py with huggingface_hub542c3ba6.6 KB
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  6. 2026-10-12Upload README.md with huggingface_hub30022a06.6 KB
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  7. 2026-10-12Upload MinusData_Rejected_Log.csv with huggingface_hub174e4790 B
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  8. 2026-10-12Upload penalty_config.json with huggingface_hub87e2c600 B
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  9. 2026-10-12Upload MinusData_Chem_Negative_PoC.parquet with huggingface_huba4414db0 B
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  10. 2026-10-12initial commitf82b6030 B
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Metadata

License
cc-by-4.0

Download the dataset

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Copy any of these snippets into your notebook or terminal. All three fetch directly from Hugging Face using your own credentials.

Recommended: datasets library (Python)
from datasets import load_dataset
ds = load_dataset("Hao13911949273/MinusData-Chem-Negative-PoC")
Raw snapshot (Python)
from huggingface_hub import snapshot_download
snapshot_download(repo_id="Hao13911949273/MinusData-Chem-Negative-PoC", repo_type="dataset")
git clone (requires git-lfs)
git clone https://huggingface.co/datasets/Hao13911949273/MinusData-Chem-Negative-PoC
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