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Contributions submitted for the Student Prize

Failure Passports: Turning Model Limits into Collective Intelligence

Anıl Göktaş

November 1, 2026 at 3:01:38 PM

Ankara University, Turkey - individual applicant; institution not yet listed among participating groups

Failure Passports would make the tested limits of human-body submodels reusable: recording biological context, assumptions, parameter provenance, and failed or untested predictions. A prospective six-month BioModels pilot would compare structured passports and a compatibility checker against flat documentation containing identical facts, measuring incompatibility detection, false alarms, review time, and calibration. Open evidence, contributor credit, and author correction would turn isolated failures into shared scientific knowledge.

AI-assisted science needs a collective verification network

Luca Maria Del Bono

September 27, 2026 at 2:58:10 PM

La Sapienza University, Rome

Artificial intelligence (AI) is already changing radically the way scientific research is carried out. Programming, numerical calculations, literature searches, data analysis, or the exploration of alternative hypotheses are increasingly being delegated to AI systems. This allows scientist to focus on more higher level and creative-based tasks. Originally submitted on Sept 2, 2026

A Federated, AI-Curated Clinical Knowledge Archive for Diagnosis and Research

Stefano Bae

September 27, 2026 at 2:56:28 PM

La Sapienza University, Rome

Individual hospitals and clinicians generate a continuous stream of disease, diagnosis and treatment data, but no single institution can turn it into a systematic, reusable body of knowledge. This proposal outlines an AI-assisted pipeline that converts distributed, heterogeneous clinical records into a unified, freely accessible archive, which can serve both clinical diagnosis and biomedical research, and can act as empirical grounding for broader collective efforts to build comprehensive models of the human body. Originally submitted on Sept 7, 2026

From Instruments to Reusable Data: an AI Layer for Experimental Data Capture and Reuse

Francesco D'Amico

September 27, 2026 at 2:53:43 PM

La Sapienza University, Rome

Experiments often generate far more raw information than is used in the final analysis or publication. Data are usually selected for the original scientific question, while unused measurements, acquisition metadata, intermediate outputs and experimental context may remain local, poorly documented, or never become searchable. This limits reproducibility and wastes potentially valuable data precisely when biology increasingly needs large, heterogeneous datasets for AI and virtual-cell models. Originally submitted on Sept 3, 2026

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