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25429730
Are group 2 innate lymphoid cells ( ILC2s ) increased in chronic rhinosinusitis with nasal polyps or eosinophilia?
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25433161
Does vagus nerve contribute to the development of steatohepatitis and obesity in phosphatidylethanolamine N-methyltransferase deficient mice?
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25445714
Does psammaplin A induce Sirtuin 1-dependent autophagic cell death in doxorubicin-resistant MCF-7/adr human breast cancer cells and xenografts?
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25431941
Is methylation of the FGFR2 gene associated with high birth weight centile in humans?
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25432519
Do tumor-infiltrating immune cell profiles and their change after neoadjuvant chemotherapy predict response and prognosis of breast cancer?
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25440440
Is hidradenitis suppurativa a systemic disease with substantial comorbidity burden : a chart-verified case-control analysis?
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25444977
Does reference range for serum and salivary testosterone in young men of Mediterranean region?
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25429648
Are secretory phospholipases A2 secreted from ciliated cells and increase mucin and eicosanoid secretion from goblet cells?
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25424148
Is admission hyperglycemia associated with failed reperfusion following fibrinolytic therapy in patients with STEMI : results of a retrospective study?
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25447560
Do systematic Reviews Published in Emergency Medicine Journals Routinely Search Clinical Trials Registries : A Cross-Sectional Analysis?
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25447567
Do obese patients with idiopathic pulmonary fibrosis have a higher 90-day mortality risk with bilateral lung transplantation?
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25445624
Does promoter variant rs2301228 on the neural cell adhesion molecule 1 gene confer risk of schizophrenia in Han Chinese?
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25445628
Are [ Higher nitric oxide levels associated with disease activity in Egyptian rheumatoid arthritis patients ]?
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Embedpress: mixedbread large on the PubmedQA queries dataset

This is the query portion of the PubmedQA dataset, embedded with Mixedbread AI's mixedbread-ai/mxbai-embed-large-v1. For each document, we take the first 510 tokens (the model's max length -2 special tokens), and embed it, not using any instructions. Because the model was trained using Matryoshka Representation Learning, these embeddings can safely be truncated.

These are mainly useful for large-scale knowledge distillation.

The dataset consists of 272k rows, each row has three keys:

  • id: the original id in the fineweb sample
  • embedding: The 1024-dimensional embedding
  • text: The original text, truncated to the slice that was actually seen by the model

Because we truncate the original text, this can be directly used for training in, e.g., sentence-transformers, without having to worry about manually truncating text, matching etc.

Acknowledgments

Thanks Mixedbread AI for a GPU grant for research into small retrieval models.

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