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#understandable

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MrsNo1Special

Cybersecurity policies are often built on the ideals of uniformity, predictability, and control — understandable qualities in an industry where structure defends against chaos. But this rigid design can unintentionally alienate some of the most innovative thinkers in the field....

medium.com/@mrsno1special/neur

# #cybersecurity #policies #ideals #control #understandable

Medium · Neurodivergence and Security Policy: Are One-Size-Fits-All Rules Excluding Brilliant Minds?By MrsNo1Special
bffo

From #arXiv | From #FAIR to #CURE: Guidelines for Computational #Models of Biological #Systems | #OpenScience #FAIR #CURE #Credible #Understandable #Reproducible #Extensible #Biology #Bioinformatics 🧬 🖥️ 🧪 🔓
⬇️
arxiv.org/abs/2502.15597
arxiv.org/abs/2502.15597

arXiv logo
arXiv.orgFrom FAIR to CURE: Guidelines for Computational Models of Biological SystemsGuidelines for managing scientific data have been established under the FAIR principles requiring that data be Findable, Accessible, Interoperable, and Reusable. In many scientific disciplines, especially computational biology, both data and models are key to progress. For this reason, and recognizing that such models are a very special type of 'data', we argue that computational models, especially mechanistic models prevalent in medicine, physiology and systems biology, deserve a complementary set of guidelines. We propose the CURE principles, emphasizing that models should be Credible, Understandable, Reproducible, and Extensible. We delve into each principle, discussing verification, validation, and uncertainty quantification for model credibility; the clarity of model descriptions and annotations for understandability; adherence to standards and open science practices for reproducibility; and the use of open standards and modular code for extensibility and reuse. We outline recommended and baseline requirements for each aspect of CURE, aiming to enhance the impact and trustworthiness of computational models, particularly in biomedical applications where credibility is paramount. Our perspective underscores the need for a more disciplined approach to modeling, aligning with emerging trends such as Digital Twins and emphasizing the importance of data and modeling standards for interoperability and reuse. Finally, we emphasize that given the non-trivial effort required to implement the guidelines, the community moves to automate as many of the guidelines as possible.
bffo

From #arXiv | From #FAIR to #CURE: Guidelines for Computational #Models of Biological #Systems | #OpenScience #FAIR #CURE #Credible #Understandable #Reproducible #Extensible #Biology #Bioinformatics 🧬 🖥️ 🧪 🔓
⬇️
arxiv.org/abs/2502.15597
arxiv.org/abs/2502.15597

arXiv logo
arXiv.orgFrom FAIR to CURE: Guidelines for Computational Models of Biological SystemsGuidelines for managing scientific data have been established under the FAIR principles requiring that data be Findable, Accessible, Interoperable, and Reusable. In many scientific disciplines, especially computational biology, both data and models are key to progress. For this reason, and recognizing that such models are a very special type of 'data', we argue that computational models, especially mechanistic models prevalent in medicine, physiology and systems biology, deserve a complementary set of guidelines. We propose the CURE principles, emphasizing that models should be Credible, Understandable, Reproducible, and Extensible. We delve into each principle, discussing verification, validation, and uncertainty quantification for model credibility; the clarity of model descriptions and annotations for understandability; adherence to standards and open science practices for reproducibility; and the use of open standards and modular code for extensibility and reuse. We outline recommended and baseline requirements for each aspect of CURE, aiming to enhance the impact and trustworthiness of computational models, particularly in biomedical applications where credibility is paramount. Our perspective underscores the need for a more disciplined approach to modeling, aligning with emerging trends such as Digital Twins and emphasizing the importance of data and modeling standards for interoperability and reuse. Finally, we emphasize that given the non-trivial effort required to implement the guidelines, the community moves to automate as many of the guidelines as possible.
Continued thread
NASTITI SZN ✨️💙💕

Teknologi itu sangat membantu memang. Tapi jangan biarkan kita malah jadi ketergantungan seperti ilustrasi di atas sampai jadi mati nalar 🙏 gak jalan itu critical thinking-nya, masak jawaban dari CGPT dikopas 100% plek ketiplek ((( SINCE I AM AN AI ASSISTANT ))) 🤣🤣🤣 peak comedy indeed #punintended 🤪😋

Kalau gue sih memperlakukan CGPT itu sebagai sarana utk memvalidasi argumen yg telah dibangun sebelumnya, bener gak sihh susunan kata2nya, sounds makes sense kah bila terbaca gituuu #understandable

Replied in thread
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PSiReN-X :verified_paw:​

#Tangentially...

#IF (and #IT's another #VeryBIG #IF) you're in #TwoMinds about #BadLoserDen and his #DeadInstance; that's #OK, #IT's #Understandable...

#AskHim #WHY I left #Syzito to set-up #PSiReN.eu and also #AskHim #WHY it took ​over 17-hours for him to pull #CovidMisinformation "published/platformed" by his #SoleSponsors (provided vicariously by a #Notorious #RightWingNutJob)...

Or... #DontBother; #IT's what happens when you have #ZeroIntegrity and #ZeroCredibility...

#TrueFacts

🐺​

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