Unverified50% confidenceFactExact time
Under temporal evaluation, no machine learning model significantly surpassed the station-month climatology baseline (improvement of no more than 0.8 percentage points).
1
Sources
50%
Confidence
Long-term
Relevance
10/30/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedThe experiment compared Jev in zero-shot and few-shot settings against 11 classical machine learning models.65% similarUnverified当模型对某个训练样本的预测概率接近1时，该样本对应的交叉熵损失趋近于零，模型几乎无法获得梯度更新信号64% similarUnverifiedIn machine learning, the equivalence margin can be set based on the practical meaning of the metric, for example, an AUROC difference of no more than 0.01.62% similarUnverifiedThe Spearman correlation coefficient between tool description scores and correct model selection was only 0.04, with almost no statistical association.61% similarUnverifiedThe pre-registered hypothesis H2 (that more thinking is harmful on the distractor counting task) was not significantly supported, with no model performing significantly worse at high.60% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1114805API
curl https://kongchang.com/api/v1/knowledge/claims/1114805MCP
get_claim(id=1114805)