{"id":"W2401761585","doi":"","title":"TAC 2010 Summarization Track - Update Summarization with Interview Algorithm.","year":2010,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Automatic summarization; Computer science; Track (disk drive); Algorithm; Data mining; Information retrieval; Artificial intelligence; Operating system","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005340186,0.0001347591,0.0001585371,0.00008796949,0.0002461263,0.0001024159,0.0004823998,0.00007241416,0.00003569854],"category_scores_gemma":[0.0000150922,0.0001038911,0.00002239676,0.0003758029,0.0002391932,0.0007574827,0.0001833419,0.0001561238,0.00001100226],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003914102,"about_ca_system_score_gemma":0.00003809731,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000165224,"about_ca_topic_score_gemma":0.00001247632,"domain_scores_codex":[0.9991154,0.00007666746,0.0002321095,0.000295126,0.0001480221,0.0001326724],"domain_scores_gemma":[0.9988444,0.00010932,0.0001693673,0.0006355505,0.0001723701,0.00006894725],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000007461997,0.00004344871,0.00007243711,0.00001911455,0.000008171278,2.137506e-7,0.0001470303,0.000005286598,0.0008331274,0.7002062,0.00007896509,0.2985785],"study_design_scores_gemma":[0.001089463,0.0002478543,0.005239478,0.00008013494,0.0001067981,0.00006508523,0.0004369544,0.02223753,0.04755251,0.7316783,0.1903865,0.0008793242],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002155886,0.0002146339,0.9962621,0.0002284871,0.0001001564,0.0002734147,0.00002723426,0.00009853799,0.000639574],"genre_scores_gemma":[0.7011768,0.0005892934,0.2956513,0.0002570852,0.0002828259,0.0003652567,0.0006453578,0.00003860468,0.000993408],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7006108,"threshold_uncertainty_score":0.4236557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00681810827578963,"score_gpt":0.2289243610219437,"score_spread":0.2221062527461541,"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."}}