{"id":"W1538369613","doi":"10.1007/978-3-540-72665-4_25","title":"Question Answering Summarization of Multiple Biomedical Documents","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Topic Modeling","field":"Computer Science","cited_by":47,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Automatic summarization; Information retrieval; Computer science; Question answering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001193977,0.0002984011,0.0003527491,0.0009392006,0.0001030778,0.0001539265,0.00188206,0.0003092442,0.000009241274],"category_scores_gemma":[0.000157999,0.0002893763,0.0000744452,0.0005282739,0.0003926484,0.0005473663,0.0008771615,0.0004455564,0.000008744108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002418656,"about_ca_system_score_gemma":0.0002745294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007775422,"about_ca_topic_score_gemma":0.00006389743,"domain_scores_codex":[0.9968176,0.00002424543,0.0006107264,0.001005319,0.001106897,0.0004351695],"domain_scores_gemma":[0.9981533,0.0002902929,0.0002977454,0.0009176112,0.0002076599,0.0001333852],"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":[0.00000417292,0.00002851039,0.0004612435,0.00005526784,0.000006808057,0.00002985937,0.0004736228,0.02973777,0.0008088511,0.0182444,0.000002759273,0.9501467],"study_design_scores_gemma":[0.0002430306,0.0000892035,0.0001962987,0.0004854202,0.000004132117,0.00001849936,8.560656e-8,0.9537559,0.002485979,0.04175048,0.000639618,0.000331414],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003215067,0.0001491108,0.9963671,0.0001502465,0.001719685,0.0002345481,0.000002012042,0.0001060334,0.0009497416],"genre_scores_gemma":[0.2984238,0.00002579143,0.7008668,0.0002513693,0.0002955562,0.000002337369,0.000008673183,0.00001862267,0.0001070651],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9498153,"threshold_uncertainty_score":0.9999558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02123581115807662,"score_gpt":0.2743989315989915,"score_spread":0.2531631204409149,"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."}}