Bovine noroviruses antibody and antigen (recombinant protein)
Diagnostic anti-Bovine noroviruses antibodies pairs and antigen for animal health (animal Bovines/Cattle infectious disease nonbacterial diarrheic disease) testing in ELISA, colloidal gold-based Lateral flow immunoassay (LFIA), CLIA, TINIA and POCT
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Product information
Catalog No. | Description | US $ Price (per mg) |
---|---|---|
GMP-VT-P093-Ag01 | Recombinant Bovine noroviruses protein | $3090.00 |
GMP-VT-P093-Ab01 | Anti-Bovine noroviruses mouse monoclonal antibody (mAb) | $3090.00 |
GMP-VT-P093-Ab02 | Anti-Bovine noroviruses mouse monoclonal antibody (mAb) | $3090.00 |
Size: 1mg | 10mg | 100mg
Product Description
Cat No. | GMP-VT-P093-Ag01 |
Product Name | Recombinant Bovine noroviruses protein |
Pathogen | Bovine noroviruses |
Expression platform | E.coli |
Isotypes | Recombinant Antigen |
Bioactivity validation | Anti-Bovine noroviruses antibodies binding, Immunogen in Sandwich Elisa, lateral-flow tests, and other immunoassays as control material in Bovine noroviruses level test of animal Bovines/Cattle infectious disease with nonbacterial diarrheic disease. |
Tag | His | Product description | Recombinant Bovine noroviruses proteinwas expressed in E.coli - based prokaryotic cell expression system and is expressed with 6 HIS tag at the C-terminus. |
Purity | Purity: ≥95% (SDS-PAGE) |
Application | Paired antibody immunoassay validation in Sandwich ELISA, ELISA, colloidal gold-based Lateral flow immunoassay (LFIA), CLIA, TINIA, POCT and other immunoassays. |
Formulation | Lyophilized from GM's Protein Stability Buffer2 (PSB2,Confidential Ingredients) or PBS (pH7.4); For PSB2, reconstituted with 0.9% sodium chloride; For PBS, reconstituted with ddH2O. |
Storage | Store at -20℃ to -80℃ under sterile conditions. Avoid repeated freeze-thaw cycles. |
Cat No. | GMP-VT-P093-Ab01,GMP-VT-P093-Ab02 |
Pathogen | Bovine noroviruses |
Product Name | Anti-Bovine noroviruses mouse monoclonal antibody (mAb) |
Expression platform | CHO |
Isotypes | Mouse IgG |
Bioactivity validation | Recombinant Bovine noroviruses antigen binding, ELISA validated as capture antibody and detection antibody. Pair recommendation with other anti-Bovine noroviruses antibodies in Bovine noroviruses level test of animal Bovines/Cattle infectious disease with nonbacterial diarrheic disease. |
Product description | Anti-Bovine noroviruses mouse monoclonal antibody (mAb) is a mouse monoclonal antibody produced by CHO technology. The antibody is ELISA validated as capture antibody and detection antibody. Pair recommendation with other anti-Bovine noroviruses antibodies./td> |
Purity | Purity: ≥95% (SDS-PAGE) |
Application | Paired antibody immunoassay validation in Sandwich ELISA, ELISA, colloidal gold-based Lateral flow immunoassay (LFIA), CLIA, TINIA, POCT and other immunoassays. |
Formulation | Lyophilized from GM's Protein Stability Buffer2 (PSB2,Confidential Ingredients) or PBS (pH7.4); For PSB2, reconstituted with 0.9% sodium chloride; For PBS, reconstituted with ddH2O. |
Storage | Store at -20℃ to -80℃ under sterile conditions. Avoid repeated freeze-thaw cycles. |
Reference
Validation Data
Click to get more Data / Case study about the product.
Pathogen
An AI model's knowledge cutoff refers to the point in time when the training data for that model stops. In the case of my predecessor GPT-3.5, the knowledge cutoff was in September 2021. This means that the model was not trained on or exposed to any data, events, or developments that occurred after that date. Understanding the knowledge cutoff is essential for various reasons, and it has several implications for the use and limitations of the model.
First, it's crucial to acknowledge that AI models, including GPT-3.5, are not capable of accessing or retrieving information beyond their knowledge cutoff. This limitation arises because they do not have real-time internet access or the ability to update themselves with new information. This has clear implications for the model's ability to provide up-to-date information on current events, emerging trends, or recent scientific discoveries. Users should be aware that the model's responses may not reflect the latest developments in a particular field or current affairs.
Second, the knowledge cutoff affects the accuracy and reliability of information provided by the model. While the model has been trained on a vast and diverse dataset up to September 2021, the accuracy of its responses may decline when applied to topics that have evolved significantly since then. For example, if you ask about the most recent advances in a rapidly changing field like artificial intelligence, the model's responses may not be as accurate as those from a model with more current training data.
Third, the knowledge cutoff underscores the importance of critical thinking and verification when using AI models. Users should not blindly trust the information provided by the model and should cross-reference it with up-to-date and reliable sources. Fact-checking and critical evaluation of the responses are essential steps to ensure the accuracy of the information obtained from the model.
Fourth, it's worth noting that the knowledge cutoff affects various domains, including scientific, technological, cultural, and geopolitical knowledge. In fields where developments occur rapidly, such as biotechnology or space exploration, the model's limitations are particularly evident. For cultural references, the model may not be aware of recent movies, music, or internet memes that have gained popularity after its knowledge cutoff.
Fifth, the knowledge cutoff can impact ethical considerations when using AI. For instance, in discussions about sensitive current events, political issues, or ongoing crises, users should be cautious and consider that the model's responses may not be informed by the most recent developments or nuanced perspectives.
In summary, understanding an AI model's knowledge cutoff is fundamental for its responsible use. It helps users recognize the limitations of the model in terms of providing up-to-date and accurate information. It also emphasizes the importance of independent verification and critical thinking when using the model as a source of information. While AI models like GPT-3.5 can be valuable tools for generating ideas, explanations, and insights, users should always consider the context and the model's training limitations when relying on its responses, particularly when dealing with topics or events that have evolved after its last training data update in September 2021.
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