{"id":"W2114562718","doi":"10.1613/jair.2784","title":"Complex Question Answering: Unsupervised Learning Approaches and Experiments","year":2009,"lang":"en","type":"article","venue":"Journal of Artificial Intelligence Research","topic":"Topic Modeling","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; University of Lethbridge","keywords":"Automatic summarization; Set (abstract data type); Tree kernel; Weighting; Relevance (law); Unsupervised learning; ENCODE; Kernel (algebra); Feature (linguistics)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007609872,0.001305367,0.001321964,0.001293766,0.001023619,0.001128085,0.002311356,0.002219492,0.003726878],"category_scores_gemma":[0.02473403,0.0004371383,0.0009391369,0.00192554,0.001457736,0.002491039,0.001779888,0.002207145,0.001511545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00120404,"about_ca_system_score_gemma":0.001085043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005965608,"about_ca_topic_score_gemma":0.005100782,"domain_scores_codex":[0.9930671,0.003711011,0.00050669,0.001260379,0.001135743,0.0003190203],"domain_scores_gemma":[0.9679272,0.02427766,0.0009500502,0.004033251,0.00219508,0.0006166896],"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":[0.004459819,0.01583998,0.02263948,0.002820956,0.001033636,0.0008266335,0.002463229,0.401255,0.01849634,0.009668214,0.03242521,0.4880715],"study_design_scores_gemma":[0.0006158579,0.001282715,0.009758797,0.00009425888,0.000116575,0.0004533043,0.0006178172,0.9486945,0.01522854,0.01461949,0.008398741,0.000119339],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7591165,0.00214536,0.2102213,0.0009057515,0.0002928794,0.002932064,0.005543916,0.005009597,0.01383272],"genre_scores_gemma":[0.7684226,0.0006208124,0.2116085,0.0005664285,0.0001620645,0.002077205,0.01208814,0.0004513811,0.004002939],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007609872,"threshold_uncertainty_score":0.04024535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4485195580979168,"score_gpt":0.4474377941188779,"score_spread":0.001081763979038919,"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."}}