{"id":"W2517601353","doi":"10.1109/icdec.2016.7563143","title":"BubbleNet: An innovative exploratory search and summarization interface with applicability in health social media","year":2016,"lang":"en","type":"article","venue":"","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Alberta Innovates","keywords":"Automatic summarization; Computer science; Exploratory search; Information retrieval; Social media; World Wide Web; Interface (matter); Semantic search; Graph; Exploratory research; Search engine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005938191,0.0000760814,0.0001318703,0.00007579998,0.00005585247,0.00004077169,0.0002371454,0.00003630475,0.00000516292],"category_scores_gemma":[0.0000392273,0.00004413295,0.000004155901,0.000434644,0.0001372409,0.000528958,0.0001426809,0.00005908742,0.000003210035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005820985,"about_ca_system_score_gemma":0.0001572618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001342548,"about_ca_topic_score_gemma":0.002083175,"domain_scores_codex":[0.9990481,0.0001374568,0.0001595144,0.0003131893,0.0001492793,0.0001924857],"domain_scores_gemma":[0.9994878,0.0001431667,0.00003404343,0.0001883391,0.00009977527,0.00004684316],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00007645288,0.0001784849,0.1118948,0.00005480707,0.00001005531,0.00000342817,0.03734059,0.000008484152,0.00213946,0.1195311,0.0001283947,0.7286339],"study_design_scores_gemma":[0.002908688,0.0009321472,0.9424146,0.0001243256,0.00000153506,0.000007218153,0.00868985,0.00746896,0.02006602,0.01606087,0.0006900619,0.0006357677],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.536965,0.00002198099,0.459691,0.002994919,0.00002366477,0.0001117533,8.801776e-7,0.00006880736,0.0001219713],"genre_scores_gemma":[0.9907715,0.00001173052,0.009012152,0.0001546462,0.0000194084,0.00001254353,7.384229e-7,0.000003401903,0.00001384553],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8305198,"threshold_uncertainty_score":0.179969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04351433390483602,"score_gpt":0.2998404350214005,"score_spread":0.2563261011165645,"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."}}