{"id":"W4385339878","doi":"10.1007/978-3-031-39841-4_7","title":"Ontology-Driven Parliamentary Analytics: Analysing Political Debates on COVID-19 Impact in Canada","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Topic Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Ontology; Computer science; Analytics; Context (archaeology); Vocabulary; World Wide Web; Data science; Linguistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001945795,0.0002186155,0.0004025656,0.003711137,0.00379921,0.00573747,0.001166814,0.0007032956,0.004447955],"category_scores_gemma":[0.01188439,0.0002301433,0.0003825606,0.01226623,0.001922312,0.002377848,0.001519443,0.001200819,0.0005473875],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04551197,"about_ca_system_score_gemma":0.05005351,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9860662,"about_ca_topic_score_gemma":0.9907317,"domain_scores_codex":[0.9985663,0.0002621044,0.00004854737,0.0001540904,0.0005577607,0.0004111137],"domain_scores_gemma":[0.9937155,0.003050801,0.0004233179,0.0002487023,0.002129822,0.0004319152],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005843319,0.0002174569,0.3720026,0.0005618019,0.0002359995,0.0006363848,0.07593468,0.03458942,0.002140607,0.2467126,0.08814202,0.1782421],"study_design_scores_gemma":[0.00003826993,0.00003066208,0.4594223,0.0003913653,0.0001290077,0.00008474156,0.1489446,0.1050697,0.00226357,0.035298,0.2481489,0.0001788931],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9038813,0.001212362,0.006591669,0.003696126,0.00006517008,0.00009220267,0.01087341,0.0002623138,0.07332556],"genre_scores_gemma":[0.9828026,0.0003440506,0.003078504,0.0001083842,0.00001384377,0.00003415818,0.004726163,0.0001312283,0.008761139],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04551197,"threshold_uncertainty_score":0.330214,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03953028108057926,"score_gpt":0.2981980090836647,"score_spread":0.2586677280030854,"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."}}