{"id":"W2101916644","doi":"","title":"The Alyssa System at TAC QA 2008","year":2008,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Topic Modeling","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Component (thermodynamics); Track (disk drive); Entertainment; Information retrieval; Physics; Operating system; Law; Political science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006201586,0.001064742,0.001250904,0.002405149,0.001496598,0.003141572,0.002207911,0.00204188,0.03003626],"category_scores_gemma":[0.009195809,0.0007159598,0.0007632872,0.001767193,0.0007589076,0.004457084,0.002266459,0.002050207,0.01844908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001940704,"about_ca_system_score_gemma":0.002048513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02424341,"about_ca_topic_score_gemma":0.01580457,"domain_scores_codex":[0.9963925,0.001323678,0.000254834,0.000773741,0.0009931909,0.0002620397],"domain_scores_gemma":[0.9940514,0.001373386,0.0001827125,0.001091757,0.0028019,0.0004987559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002905002,0.001089789,0.005133823,0.001353074,0.0002606026,0.0005069664,0.001832971,0.01206719,0.03384407,0.008364448,0.6696031,0.263039],"study_design_scores_gemma":[0.002412842,0.001187591,0.009891707,0.0002248571,0.0003071325,0.0006467786,0.000963877,0.3392592,0.05444393,0.01337318,0.5769475,0.0003415001],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"empirical","genre_scores_codex":[0.1732191,0.003718034,0.2183142,0.005571667,0.002206117,0.002673935,0.07373334,0.4619841,0.05857946],"genre_scores_gemma":[0.4798637,0.000718319,0.2573322,0.002466511,0.0008170796,0.001236645,0.1994076,0.009081378,0.04907661],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03003626,"threshold_uncertainty_score":0.1004813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01124295826853213,"score_gpt":0.2223069812998208,"score_spread":0.2110640230312887,"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."}}