Team-Feedback-Konsole
Reason tags
Aktive Gewichte
Erfahrung24.0%
Startup-Geschwindigkeit18.0%
PI-Kapazitaet14.0%
Competitor-Abdeckung14.0%
CTGov-Relevanz16.0%
Operative Stabilitaet10.0%
Sponsor-Fit4.0%
prototype 02
Site Feasibility mit Team-Feedback
Team-Policy lernt aus Multi-User-Feedback. Serielle Single-User-Dislikes werden gedeckelt; Gewichtsanpassungen brauchen Konsens.
Basis-Filterkontext
Vorher (Team-Basis)
#1 Local Institution
Seoul, South Korea
score: 66.2
#2 Local Institution
Hangzhou, China
score: 62.8
#3 Samsung Medical Center
Seoul, South Korea
score: 52
#4 Local Institution
Beijing, China
score: 49.5
#5 Local Institution
Guangzhou, China
score: 49.5
#6 Local Institution
Shanghai, China
score: 49.5
#7 National Taiwan University Hospital
Taipei, Taiwan
score: 38.1
#8 Memorial Sloan Kettering Cancer Center
New York, United States
score: 34.1
Nachher (gelernte Team-Policy)
#1 Local Institution
Seoul, South Korea
score: 66.2
#2 Local Institution
Hangzhou, China
score: 62.8
#3 Samsung Medical Center
Seoul, South Korea
score: 52
#4 Local Institution
Beijing, China
score: 49.5
#5 Local Institution
Guangzhou, China
score: 49.5
#6 Local Institution
Shanghai, China
score: 49.5
#7 National Taiwan University Hospital
Taipei, Taiwan
score: 38.1
#8 Memorial Sloan Kettering Cancer Center
New York, United States
score: 34.1
Rangverschiebung
#1 Local Institutionafter #1 (0)
#2 Local Institutionafter #2 (0)
#3 Samsung Medical Centerafter #3 (0)
#4 Local Institutionafter #4 (0)
#5 Local Institutionafter #5 (0)
#6 Local Institutionafter #6 (0)
#7 National Taiwan University Hospitalafter #7 (0)
#8 Memorial Sloan Kettering Cancer Centerafter #8 (0)
#9 Local Institutionafter #9 (0)
#10 Local Institutionafter #10 (0)
Konsens-Schutzregeln
Feedback-Log (Audit)
Noch kein Feedback.
update log
Prototype Change Log
2026-03-01 · v0.3.0
Team-Policy-Persistenz und Konsens-Aggregation
- - Persistente Team-Profile und serverseitiger Feedback-Event-Store hinzugefuegt.
- - Multi-User-Konsens-Aggregation fuer aktive Gewichtsanpassung integriert.
- - Anti-Missbrauchsregeln ergaenzt: Tages-Cap pro User, Abklingfaktor bei Serienfeedback, max. Shift pro Dimension.
2026-03-01 · v0.2.0
Human-Feedback-Verstaerkung hinzugefuegt
- - Before-vs-after Ranking-Vergleich hinzugefuegt.
- - Explizite Feedback-Aktionen (like/dislike) mit Gruenden eingebaut.
- - Adaptive Gewichtsanpassung plus Audit-Log integriert.