{"id":"W3186310017","doi":"10.18653/v1/2021.semeval-1.48","title":"CLaC-np at SemEval-2021 Task 8: Dependency DGCNN","year":2021,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; SemEval; Dependency (UML); Artificial intelligence; Natural language processing; Lexical analysis; Preprocessor; Task (project management); Variety (cybernetics); ENCODE; Graph; Dependency graph; Theoretical computer science","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":[0.002276341,0.003644293,0.001466702,0.001077169,0.001421472,0.002182518,0.002991622,0.004914097,0.03530287],"category_scores_gemma":[0.009892116,0.0006979181,0.001763647,0.001101456,0.0006801407,0.004484251,0.002623425,0.005133244,0.02170438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001777016,"about_ca_system_score_gemma":0.001994205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01483933,"about_ca_topic_score_gemma":0.02000684,"domain_scores_codex":[0.9982002,0.0003918901,0.00008196472,0.0008064816,0.0002384612,0.0002809275],"domain_scores_gemma":[0.9965275,0.001589188,0.0001190493,0.0008209575,0.000715475,0.000227773],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001506502,0.0007864069,0.005059825,0.00127585,0.0003105608,0.001447528,0.0003848337,0.02201171,0.01315924,0.00825463,0.6602568,0.2855462],"study_design_scores_gemma":[0.0009357285,0.0008850922,0.01134788,0.0004232907,0.000244153,0.001824172,0.0008245463,0.6474656,0.05227964,0.04612514,0.2374187,0.0002261555],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3446932,0.005241951,0.1632294,0.007574435,0.006876114,0.002822786,0.236892,0.1187985,0.1138717],"genre_scores_gemma":[0.4871244,0.0004514787,0.1214241,0.002558787,0.0005600711,0.002244871,0.3314012,0.006019176,0.0482159],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03530287,"threshold_uncertainty_score":0.1180999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01922293793452172,"score_gpt":0.242899614600191,"score_spread":0.2236766766656693,"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."}}