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Bug Reported on Thursday, 4 June 2026 at 11:55:58 am IST in
Lab - Machine Learning Virtual Laboratory Experiment - Binary Classification and Decision Boundary Analysis using
Logistic Regression
Type(s) ...
DLBG
vlabs-bug
Parent : #82 · Phase H4
Objectif
Verrouiller et mettre en prod.
Tâches
- [ ] CORS restreint au domaine choix-narratifs (le relais ne sert que ce client ; les routes /v1/suggest gardent leur
politique). ...
RebelliousSmile
In v2/templates/admin_statements.html, there is a note:
For advanced operations not available here, use the [Polis admin interface](…/m/ conversation_id ) (requires a Polis
account).
The link points ...
lgelauff
Probleme und Engpässe beim ersten Prototyp erkennen. Testfälle erstellen und auswerten.
Zeitaufwand: 4h
silasb-dev
Executive Summary
AI-Health-Monitoring fuses data from multiple wearable sensors (ECG, PPG, accelerometer, temperature) but assumes
perfect time synchronization. Real wearables have clock skew, jitter, ...
anshul23102
Executive Summary
AI-Health-Monitoring runs heavy TensorFlow models on resource-constrained wearables. Continuous inference consumes
excessive CPU, draining battery 10x faster than acceptable. Users must ...
Executive Summary
Wearable sensors degrade over time: electrode contact worsens, batteries weaken, firmware updates change calibration. ML
model trained on fresh sensors performs poorly on degraded sensors. ...
Executive Summary
AI-Health-Monitoring transmits health data (heart rate, ECG, blood pressure, sleep patterns) from wearable to app
without end-to-end encryption. Attacker on network can intercept and ...
Parent : #82 · Phase H3
Objectif
Authentifier le relais et facturer la génération en Muses.
⚠️ Bloqueur
Aucun système de portefeuille Muse n existe encore dans le repo (seul client.py porte le mode ...
Executive Summary
AI-Health-Monitoring uses ML models for health anomaly detection but lacks clinical validation. Models trained on
limited datasets may give false positives/negatives. Users may act on ...
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