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Table 6: 
MCC results for specific phenomena. Emb. is model embedding style; Enc. is model encoder training, Class. is model classifier training. R/F is real/fake, ELMo-St. is ELMo-style, and CoLA-Th. is threshold tuning on CoLA. LSTM LM WLPM is the LM with Lau et al. metrics Word LP Min-1.
ModelEmb.Enc.Class.SVOWhCausativeSV Agr.Reflexive
LSTM LM WLPM BNC – CoLA Th. 0.801 0.601 0.270 0.599 0.152 
 
Pooling ELMo-St. CoLA CoLA 0.637 0.102 0.633 0.128 0.075 
Pooling BNC R/F CoLA 0.381 0.184 0.463 0.098 0.043 
Pooling GloVe R/F CoLA 0.988 0.059 0.614 0.277 0.150 
Pooling ELMo-St. R/F CoLA 0.650 0.000 0.449 0.302 -0.020 
ModelEmb.Enc.Class.SVOWhCausativeSV Agr.Reflexive
LSTM LM WLPM BNC – CoLA Th. 0.801 0.601 0.270 0.599 0.152 
 
Pooling ELMo-St. CoLA CoLA 0.637 0.102 0.633 0.128 0.075 
Pooling BNC R/F CoLA 0.381 0.184 0.463 0.098 0.043 
Pooling GloVe R/F CoLA 0.988 0.059 0.614 0.277 0.150 
Pooling ELMo-St. R/F CoLA 0.650 0.000 0.449 0.302 -0.020 
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