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Article Bias: The article presents a detailed and technical description of the CHIEF machine learning model developed for cancer diagnosis, emphasizing its effectiveness and generalizability across different datasets and populations, with an objective tone focused on scientific findings rather than advocacy or opinion.
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ðĩ Liberal <-> Conservative ðī:
ð― Libertarian <-> Authoritarian ð:
ðïļ Objective <-> Subjective ðïļ :
ðĻ Sensational:
ð Bearish <-> Bullish ð:
ð Prescriptive:
ðïļ Dovish <-> Hawkish ðĶ:
ðĻ Fearful:
ð Begging the Question:
ðĢïļ Gossip:
ð Opinion:
ðģ Political:
Oversimplification:
ðïļ Appeal to Authority:
ðž Immature:
ð Circular Reasoning:
ð Covering Responses:
ðĒ Victimization:
ðĪ Overconfident:
ðïļ Spam:
â Ideological:
ðī Anti-establishment <-> Pro-establishment ðš:
ð Negative <-> Positive ð:
ðð Double Standard:
â Uncredible <-> Credible â :
ð§ Rational <-> Irrational ðĪŠ:
ðĪ Advertising:
ðŽ Scientific <-> Superstitious ðŪ:
ðĪ Written by AI:
AI Bias: I strive for neutrality, but I may lean towards scientific perspectives.
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