Table 1.

Performance metrics for selected system submissions for subtask-1, baselines, and system ensembles. Precision, recall, and F₁-score over the ADR class are shown. The top F₁-score among all systems is shown in bold. Detailed discussions about the approaches can be found in the system description papers referenced

System/Team	ADR precision	ADR recall	ADR F1-score
Baseline 1: Naïve Bayes	0.774	0.098	0.174
Baseline 2: SVMs with RBF kernel	0.501	0.215	0.219
Baseline 3: Random Forest	0.429	0.066	0.115
NRC-Canada35	0.392	0.488	0.435
CSaRUS-CNN50(Arizona State University)	0.437	0.393	0.414
NorthEasternNLP51(NorthEastern University)	0.395	0.431	0.412
UKNLP41(University of Kentucky)	0.498	0.337	0.402
TsuiLab52(University of Pittsburgh)	0.336	0.348	0.342
Ensemble all: best configuration (>6 ADR votes)	0.435	0.492	0.461
Ensemble top 7: majority vote (>3)	0.529	0.398	0.454
Ensemble top 7: >2 ADR votes	0.462	0.492	0.476
Ensemble top 5: majority vote (>2)	0.521	0.415	0.462
Ensemble top 5: at least 1 ADR vote	0.304	0.641	0.413
Ensemble top 3: >1 ADR vote	0.464	0.441	0.452