{"id":"W3022585926","doi":"10.1007/978-3-030-47358-7_11","title":"Selection Driven Query Focused Abstractive Document Summarization","year":2020,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Topic Modeling","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Automatic summarization; Computer science; ENCODE; Selection (genetic algorithm); Encoder; Artificial intelligence; Representation (politics); Mechanism (biology); Sequence (biology); Natural language processing; State (computer science); Information retrieval; Algorithm","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001077186,0.001650558,0.00182937,0.00298447,0.0008109621,0.002060735,0.001461221,0.001120305,0.01058045],"category_scores_gemma":[0.002966577,0.0004385633,0.001039904,0.003666017,0.0003135611,0.001762624,0.001171706,0.001145004,0.008003846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005087354,"about_ca_system_score_gemma":0.001060325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002310858,"about_ca_topic_score_gemma":0.004348916,"domain_scores_codex":[0.9987966,0.0002998206,0.0001352756,0.0002245495,0.0004309761,0.0001127815],"domain_scores_gemma":[0.9976361,0.0007894754,0.0001464067,0.0002936838,0.001054064,0.00008025607],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009169615,0.0002186978,0.0006545252,0.00115851,0.0002129777,0.000312252,0.0002548477,0.01020629,0.1132008,0.003059673,0.09008301,0.7797214],"study_design_scores_gemma":[0.0002772536,0.001124421,0.004953724,0.0001608534,0.001023474,0.001138318,0.0007299172,0.6442226,0.191034,0.01334956,0.1418042,0.0001817057],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0338581,0.01023616,0.9145162,0.001274385,0.001173005,0.0008406893,0.009456263,0.01967134,0.008973888],"genre_scores_gemma":[0.1787597,0.004088121,0.738144,0.0007749737,0.001599075,0.0006837116,0.03409498,0.001449903,0.04040551],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01058045,"threshold_uncertainty_score":0.03539515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01662594742091375,"score_gpt":0.238588516032867,"score_spread":0.2219625686119533,"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."}}