BioASQ Participants Area

Team Name	Run name	P	R	F1
BIT.UA	run4-everything	0.8095	0.7878	0.7985
BIT.UA	run0-lc-dense-5-wVal	0.8015	0.7878	0.7946
BIT.UA	run1-lc-dense-5-full	0.7954	0.7894	0.7924
BIT.UA	run3-PlanTL-dense-bilstm-all-wVal	0.7978	0.787	0.7923
BIT.UA	run2-lc-bilstm-all-wVal	0.7941	0.7823	0.7881
Vicomtech	run1-xlm_roberta_large_dpa_e105	0.8054	0.7535	0.7786
Vicomtech	run2-roberta_bio_es_dpa_e119	0.7679	0.7629	0.7653
SINAI	run1-fine-tuned-roberta	0.7631	0.7505	0.7568
Vicomtech	run3-longformer_base_4096_bne_es	0.7478	0.7588	0.7533
SINAI	run4-fulltext-LSTM	0.7538	0.7353	0.7444
SINAI	run2-lstmcrf-512	0.7786	0.7043	0.7396
SINAI	run5-lstm-BIO	0.7705	0.7049	0.7362
KFU NLP Team	predicted_task1	0.7192	0.7403	0.7296
SINAI	run3-fulltext-GRU	0.7396	0.711	0.725
Fusion	run4-Spanish-RoBERTa	0.7165	0.7143	0.7154
Fusion	run3-XLM-RoBERTA-Clinical	0.7047	0.6916	0.6981
NLP-CIC-WFU	Hard4BIO_RoBERTa_postprocessing	0.7188	0.654	0.6849
NLP-CIC-WFU	Hard4BIO_RoBERTa	0.7132	0.6507	0.6805
Fusion	run1-BioMBERT-NumberTagOnly	0.6948	0.6599	0.6769
Fusion	run2-BioMBERT-FullPrep	0.6894	0.6599	0.6743
Fusion	run5-Adapted-ALBERT	0.6928	0.6264	0.658
NLP-CIC-WFU	Lazy4BIO_RoBERTa_postprocessing	0.6301	0.6002	0.6148
Onto-NLP	run1-bsс-bio-ehr-pharmaconer-voting-filtered	0.7425	0.4374	0.5505
Onto-NLP	run1-bsc-bio-ehr-es-pharmaconer-voting	0.7397	0.4374	0.5497
Samy Ateia	run2-gpt-4	0.6355	0.3874	0.4814
saheelmayekar	predicted_data	0.3975	0.535	0.4561
Onto-NLP	run1-pharmaconer_filtered_with_exact_match	0.3296	0.6104	0.428
Samy Ateia	run1-gpt3.5-turbo	0.523	0.2106	0.3002

Team Name	Run name	P	R	F1
Vicomtech	run1-xlm_roberta_large_dpa_e105_sapbert	0.5902	0.5525	0.5707
Vicomtech	run2-roberta_bio_es_dpa_e119_sapbert	0.5665	0.5627	0.5646
Vicomtech	run3-roberta_bio_es_dpa_e119_sapbert_condition	0.5662	0.5625	0.5643
Vicomtech	run5-longformer_base_4096_bne_es_sapbert	0.5498	0.558	0.5539
Fusion	run4-Spanish-RoBERTa_predictions	0.5377	0.5362	0.5369
Fusion	run1-BioMBERT-NumberTagOnly_XLMRSapBERT.tsv	0.5432	0.516	0.5293
Fusion	run3-XLM-RoBERTA-XLMRSapBERT	0.5332	0.5235	0.5283
SINAI	run1-fine-tuned-roberta	0.531	0.5224	0.5267
Vicomtech	run4-roberta_bio_es_dpa_e119_sapbert_cross_encoder	0.5248	0.5213	0.523
Fusion	run2-BioMBERT-FullPrep_XLMRSapBERT	0.5332	0.5105	0.5216
Fusion	run5-Adapted-ALBERT_predictions	0.5461	0.4939	0.5187
SINAI	run2-lstmcrf-512	0.5455	0.4936	0.5183
SINAI	run5-lstm-BIO	0.5352	0.4898	0.5115
SINAI	run4-fulltext-LSTM	0.5173	0.5047	0.5109
SINAI	run3-fulltext-GRU	0.5079	0.4884	0.498
KFU NLP Team	predicted_task2	0.3917	0.4033	0.3974
Onto-NLP	run1-pharmaconer-top1	0.2742	0.508	0.3562
Onto-NLP	run1-pharmaconer-voter	0.2723	0.5044	0.3536
Onto-NLP	run1-cantemist-top1	0.2642	0.4895	0.3432
Onto-NLP	run1-ehr-top1	0.263	0.4873	0.3416
BIT.UA	run4-everything	0.3211	0.3126	0.3168
BIT.UA	run3-PlanTL-dense-bilstm-all-wVal	0.3188	0.3145	0.3166
BIT.UA	run0-lc-dense-5-wVal	0.318	0.3126	0.3153
BIT.UA	run1-lc-dense-5-full	0.3143	0.3121	0.3132
BIT.UA	run2-lc-bilstm-all-wVal	0.3133	0.3087	0.311
Samy Ateia	run2-gpt-4	0.4304	0.1282	0.1976
Samy Ateia	run1-gpt-3.5-turbo	0.4051	0.0749	0.1264

Team Name	Run name	P	R	F1
Vicomtech	run5_roberta_bio_es_dpa_e119_sapbert_condition	0.619	0.6295	0.6242
Vicomtech	run4_xlm_roberta_large_dpa_e105_sapbert	0.6371	0.6109	0.6239
Vicomtech	run1_roberta_bio_es_dpa_e119_sapbert	0.6182	0.6295	0.6238
Vicomtech	run3_longformer_base_4096_bne_es_sapbert	0.6039	0.6288	0.6161
Vicomtech	run2_roberta_bio_es_dpa_e119_sapbert_cross_encoder	0.5885	0.5917	0.5901
KFU NLP Team	predicted_task3	0.4805	0.5054	0.4927
BIT.UA	run3-PlanTL-dense-bilstm-all-wVal	0.3544	0.3654	0.3598
BIT.UA	run4-everything	0.3551	0.3619	0.3585
BIT.UA	run0-lc-dense-5-wVal	0.3517	0.3619	0.3567
BIT.UA	run1-lc-dense-5-full	0.3475	0.3612	0.3542
BIT.UA	run2-lc-bilstm-all-wVal	0.3484	0.3593	0.3537
Samy Ateia	run2-gpt-4	0.5266	0.1811	0.2695
Samy Ateia	run1-gpt3.5-turbo	0.506	0.1083	0.1785

Test Results for MedProcNER Task