{"id":"W2807476308","doi":"10.18653/v1/s18-1027","title":"uOttawa at SemEval-2018 Task 1: Self-Attentive Hybrid GRU-Based Network","year":2018,"lang":"en","type":"article","venue":"","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"TD Bank Group; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Centres of Excellence","keywords":"SemEval; Computer science; Artificial intelligence; Encoder; Convolutional neural network; Task (project management); Representation (politics); Valence (chemistry); Feature (linguistics); Character (mathematics); Natural language processing; Machine learning","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001007821,0.001870908,0.0009486913,0.0004079531,0.0007335537,0.001001574,0.001842124,0.00228749,0.005814566],"category_scores_gemma":[0.002168561,0.0005018579,0.000784869,0.0003621142,0.0004518871,0.002212547,0.001482028,0.001992068,0.002665589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009108663,"about_ca_system_score_gemma":0.0007842477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007879006,"about_ca_topic_score_gemma":0.01324447,"domain_scores_codex":[0.9994992,0.0001276924,0.00001568463,0.0002025384,0.0000612701,0.00009356074],"domain_scores_gemma":[0.9994199,0.0001649236,0.00003411977,0.0001348389,0.0001719165,0.00007429012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003129164,0.001440174,0.007483744,0.0007444554,0.0004791988,0.00103007,0.0005368845,0.1930329,0.05626342,0.007688312,0.1411645,0.5870072],"study_design_scores_gemma":[0.0001604225,0.0005108996,0.001829283,0.00003989731,0.00008627331,0.0001413491,0.0001073641,0.9465916,0.0290552,0.005959696,0.01546622,0.00005195839],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6339622,0.003684172,0.2796982,0.003571257,0.002782382,0.001174927,0.009893348,0.02642327,0.03881024],"genre_scores_gemma":[0.8165736,0.0003197164,0.1356973,0.000916875,0.000267225,0.0006598347,0.01314472,0.0007156914,0.03170495],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007879006,"threshold_uncertainty_score":0.01945162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01254369254702677,"score_gpt":0.2373444790603731,"score_spread":0.2248007865133463,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}