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01Ichlibitiche /recalldb-product-recalls-sample RecallDB — U.S. Product Recall Database (Sample) Full dataset: recalldb.dataengineered.io · $49 one-time snapshot → Buy on Stripe · the same sample on Kaggle 127,783 official recalls · 292,790 recalled products · CPSC · FDA · FSIS · NHTSA · USCG · 100% source-linked RecallDB is a normalized, provenance-tracked dataset of official U.S. federal product recalls. It joins five official source families into one relational model: CPSC consumer products, NHTSA vehicles, FDA/openFDA… See the full description on the dataset page: https://huggingface.co/datasets/Ichlibitiche/recalldb-product-recalls-sample.tabularn<1K1 likes127 downloads6d agoHugging Face02Wim-Sol /vett-cpsc-recalls Vett CPSC Product Recall Corpus Normalized U.S. Consumer Product Safety Commission (CPSC) product recall records, refreshed periodically from CPSC's live recall feed. Source: U.S. Consumer Product Safety Commission (cpsc.gov). As a work of the U.S. federal government, the underlying data is in the public domain under 17 U.S.C. Section 105, not subject to copyright. This normalization/compilation is provided by Vett (Wimberly Solutions LLC). Fields: recall_id, source… See the full description on the dataset page: https://huggingface.co/datasets/Wim-Sol/vett-cpsc-recalls.tabular1K<n<10K1 likes83 downloads4d agoHugging Face03claritystorm /nhtsa-vehicle-recalls NHTSA Vehicle Recalls 1966–March 2026 One-time dated snapshot. Recall campaign and affected-product records with defect and remedy text. Verified coverage: Recall dates: 1966-01-19 through 2026-03-26. Records: 176,073 product rows; 29,865 distinct campaign IDs. This repository contains a 1,000-row public sample, not the full package. A sample does not establish complete historical coverage. Limitations Multiple product/model rows can belong to the same campaign.… See the full description on the dataset page: https://huggingface.co/datasets/claritystorm/nhtsa-vehicle-recalls.tabulartabular-classification1K<n<10K0 likes82 downloads6d agoHugging Face04PROGU2026 /recalls-by-barcode ProductGuru — Consumer Product Recalls by Barcode (EAN/GTIN) 36,654 recall notices across 32,668 distinct retail barcodes, compiled from 11 government registers. One row per (barcode, authority, notice). 100% of rows link to the issuing authority's own notice. Why this exists Most official recall registers do not publish a barcode. Across the registers we mirror, only 29.3% of consumer-product recalls carry one — France's RappelConso publishes a barcode on 100% of… See the full description on the dataset page: https://huggingface.co/datasets/PROGU2026/recalls-by-barcode.tabulartabular-classification10K<n<100K0 likes65 downloads15d agoHugging Face05AfiadataKe /ppb-kenya-recalls-dataset PPB Kenya Recalls Structured data on medicine and medical device recalls and rapid alerts issued by the Pharmacy and Poisons Board (PPB) of Kenya, covering 2016 to 2025. Load the dataset from datasets import load_dataset # Recall notices (default) recalls = load_dataset("afiadata/ppb-kenya-recalls", "recalls") # Rapid alerts alerts = load_dataset("afiadata/ppb-kenya-recalls", "rapid_alerts") Or with pandas directly: import pandas as pd recalls =… See the full description on the dataset page: https://huggingface.co/datasets/AfiadataKe/ppb-kenya-recalls-dataset.tabularn<1K1 likes61 downloads6mo agoHugging Face06ShurongSR /pet-food-recall-risk Pet Food Recall Risk Classification A small supervised multi-label text classification dataset for categorising pet food recall and safety-alert records into risk categories. Built as an academic assignment for an Information Retrieval course. All source records come from official public recall and safety-alert portals. Task Supervised multi-label text classification. Given a structured text constructed from brand name, product description, and recall reason, predict one… See the full description on the dataset page: https://huggingface.co/datasets/ShurongSR/pet-food-recall-risk.tabulartext-classificationn<1K0 likes35 downloads5mo agoHugging Face07Aulvem /recall-radar Cross-Border Product Recall Dataset A structured, machine-readable dataset of consumer-facing product recalls in three high-stakes categories (cosmetic, baby_product, food) across three regions (US, EU, JP), drawn from four authoritative agencies. Designed for cross-border e-commerce sellers and AI shopping assistants. Overview Product recalls are scattered across CPSC's web table, FDA's RSS feed, Safety Gate's search interface, and 消費者庁's Japanese-language… See the full description on the dataset page: https://huggingface.co/datasets/Aulvem/recall-radar.tabulartext-classificationn<1K0 likes33 downloads2mo agoHugging Face08ProblemsByVin /recall-gap-index Recall-Gap Index High-complaint failure patterns that have NO corresponding NHTSA recall — defects owners report in volume that regulators never forced a fix for. Every row is cross-checked against the live NHTSA recalls API, so vehicles that WERE recalled for the component (even when our local DB missed it) are excluded. Columns column meaning year Model year make Manufacturer model Model component Failure category with no NHTSA recall… See the full description on the dataset page: https://huggingface.co/datasets/ProblemsByVin/recall-gap-index.tabular1K<n<10K0 likes17 downloads3mo agoHugging Face09ClarusC64 /clinical-quad-recall-dispersion-lag-enrollment-stall-v0.2 Clinical Quad Recall Dispersion Lag Enrollment Stall v0.2 What this is A small dataset that tests one question: Can you detect when enrollment is moving toward stall, not just under pressure? This repo focuses on trial operations. It models a system where: batch recall disrupts flow site dispersion weakens coordination replacement lag delays recovery active patient count falls under pressure Run this first Generate baseline predictions: python… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-recall-dispersion-lag-enrollment-stall-v0.2.tabulartext-classificationn<1K0 likes10 downloads6mo agoHugging Face10ClarusC64 /clinical-quad-batch-recall-site-dispersion-replacement-lag-active-patients-enrollment-stall-v0.1What this repo does This dataset models trial disruption risk from batch recall propagation. It predicts when the interaction between a batch recall event, site dispersion, replacement lag, and active patient volume produces an enrollment stall and operational pause. Core quad batch_recall_flag site_dispersion_index replacement_lag_days active_patient_count Prediction target label_enrollment_stall Row structure Each row represents a trial supply shock snapshot after a recall signal. The model… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-batch-recall-site-dispersion-replacement-lag-active-patients-enrollment-stall-v0.1.tabulartext-classificationn<1K0 likes9 downloads7mo agoHugging Face

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