{"id":"W1531174292","doi":"","title":"Domain Adaptation to Summarize Human Conversations","year":2010,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Automatic summarization; Domain adaptation; Leverage (statistics); Computer science; Domain (mathematical analysis); Adaptation (eye); Labeled data; Artificial intelligence; Natural language processing; Information retrieval; Machine learning; Classifier (UML); Psychology; Mathematics","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":[0.000135693,0.00004047018,0.00003873078,0.00005214116,0.0000885707,0.00007738324,0.0003185417,0.00002595954,0.00007970047],"category_scores_gemma":[0.0000124671,0.00003858477,0.00001563442,0.0001088948,0.000007952953,0.000203157,0.00008388445,0.00007059373,0.00014232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000939487,"about_ca_system_score_gemma":0.00002363716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002120746,"about_ca_topic_score_gemma":0.0007206728,"domain_scores_codex":[0.9995273,0.00001047453,0.00009149157,0.0001635627,0.0001082869,0.00009892352],"domain_scores_gemma":[0.9995206,0.00002308774,0.00001584935,0.0003365704,0.00003935958,0.0000645218],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[1.771132e-7,0.000006890808,0.0002874154,6.261907e-7,0.000001321304,6.113602e-7,0.001386981,0.0001663506,0.01965112,0.9739711,0.0002427588,0.004284648],"study_design_scores_gemma":[0.0009283918,0.0001087935,0.02184603,0.000009893588,0.000006040008,0.00001121326,0.0007486306,0.6332746,0.008590577,0.2272652,0.1065638,0.0006469275],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1200885,4.122804e-7,0.865344,0.002385485,0.000286292,0.00007382609,2.058027e-7,0.0001178331,0.01170343],"genre_scores_gemma":[0.5934343,3.463412e-8,0.4053806,0.0004062649,0.00003455366,0.000004974004,6.539483e-7,0.000001547603,0.0007370447],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7467059,"threshold_uncertainty_score":0.1829283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02784659043970881,"score_gpt":0.2622991977669344,"score_spread":0.2344526073272256,"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."}}