{"id":"W2034148711","doi":"10.1109/ijcnn.2013.6707027","title":"Online news topic detection and tracking via localized feature selection","year":2013,"lang":"en","type":"article","venue":"","topic":"Web Data Mining and Analysis","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Feature selection; Cluster analysis; Flexibility (engineering); Context (archaeology); The Internet; Social media; Feature (linguistics); Selection (genetic algorithm); Representation (politics); Data science; Topic model; Feature extraction; Tracking (education); Word (group theory); Artificial intelligence; Quality (philosophy); Data mining; Machine learning; World Wide Web","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00005216349,0.00006634287,0.00008435956,0.00007179198,0.0000888329,0.0002042085,0.0001311742,0.0000488203,0.00003706429],"category_scores_gemma":[0.00001580922,0.00005219001,0.00002546656,0.0003048739,0.000009255188,0.0005473818,0.00004887159,0.00008803937,0.00002298879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001311517,"about_ca_system_score_gemma":0.00000690857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009492516,"about_ca_topic_score_gemma":0.0006858556,"domain_scores_codex":[0.9994767,0.00002855756,0.00008170288,0.0002185939,0.00008290604,0.0001115387],"domain_scores_gemma":[0.9997022,0.00001894678,0.00003091881,0.0001556592,0.0000447904,0.000047514],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[6.955967e-7,0.0000249907,0.002272588,0.000004232128,0.00001359687,5.664367e-7,0.00007750034,0.00002230627,0.01091122,0.0001326777,0.0006854858,0.9858541],"study_design_scores_gemma":[0.0002828581,0.00007446605,0.03144049,0.000009272097,0.0000168002,0.00003718149,0.00007410892,0.9531726,0.007219136,0.0007791352,0.006720493,0.0001734625],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1522538,0.00003620703,0.8460439,0.001208762,0.0000659498,0.00004340601,2.706142e-7,0.0001350799,0.0002125428],"genre_scores_gemma":[0.9489254,0.00001257018,0.04920935,0.0003423029,0.00008445865,0.000003927476,0.000003790401,0.000003145313,0.001415046],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9856807,"threshold_uncertainty_score":0.2128247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01124015395231547,"score_gpt":0.2308221349626473,"score_spread":0.2195819810103318,"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."}}