{"id":"W7100476103","doi":"","title":"Canada (2013)&amp;quot; COMPRESSIVE GAUSSIAN MIXTURE ESTIMATION","year":2013,"lang":"en","type":"article","venue":"","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sketch; Histogram; Mixture model; Projection (relational algebra); Compressed sensing; Set (abstract data type); Centroid; Representation (politics); Data set","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000057061,0.0001145636,0.0001062169,0.00003642384,0.0001350138,0.000199128,0.0005134579,0.0000375443,0.0005200508],"category_scores_gemma":[0.00002973725,0.00008648138,0.00002305451,0.0001533967,0.00001487028,0.000318637,0.0001094238,0.0001687975,0.0003322678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003744777,"about_ca_system_score_gemma":0.0001837005,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7714677,"about_ca_topic_score_gemma":0.2000667,"domain_scores_codex":[0.9990906,0.00004921209,0.0001316877,0.0002444115,0.0002522681,0.0002317905],"domain_scores_gemma":[0.999283,0.00005841046,0.00006377554,0.0003935281,0.00006868925,0.0001326231],"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":[5.925208e-7,0.00002976676,0.0005586491,0.00001649673,0.00001773185,0.00001049702,0.0003271982,0.008560657,0.0001716286,0.01680866,0.7914841,0.1820141],"study_design_scores_gemma":[0.0001364911,0.0000148377,0.007376298,0.00001213848,0.000001934808,0.00001894973,0.00001125907,0.8948313,0.0001565618,0.001511656,0.09573915,0.0001894213],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005124346,0.00005989184,0.9548064,0.02357393,0.0005043737,0.0001591933,0.00000188438,0.0002200907,0.01554993],"genre_scores_gemma":[0.6840099,0.000002538335,0.294008,0.002441344,0.0001180593,0.00002299145,0.00001670301,0.000009941515,0.01937049],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8862706,"threshold_uncertainty_score":0.81453,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005871955904163193,"score_gpt":0.21664568176879,"score_spread":0.2107737258646268,"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."}}