{"id":"W6888440185","doi":"10.20382/v16i1a5","title":"Density approximation for moving groups","year":2023,"lang":"en","type":"article","venue":"Journal of Computational Geometry (Carleton University)","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Kernel density estimation; Track (disk drive); Group (periodic table); Kernel (algebra); Tracking (education); Density estimation; Maxima","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005138828,0.00008615675,0.0001540426,0.001352859,0.0001612724,0.000129966,0.0006987404,0.00003453745,0.000005107639],"category_scores_gemma":[0.00006671461,0.00009198691,0.0001333612,0.001894215,0.00002306997,0.001513003,0.0002335149,0.00009583963,0.00001813388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008343287,"about_ca_system_score_gemma":0.00007083162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001790086,"about_ca_topic_score_gemma":4.815456e-7,"domain_scores_codex":[0.9990273,0.00003861416,0.0002134785,0.0001565472,0.0003999897,0.0001640431],"domain_scores_gemma":[0.9988544,0.0002625952,0.0002983394,0.000121836,0.0003848666,0.00007795086],"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":[0.0001028187,0.0001919124,0.002149692,0.0001409948,0.0003484261,0.0003792609,0.000467375,0.2208253,0.0002459748,0.6382008,0.02285695,0.1140906],"study_design_scores_gemma":[0.002286658,0.0003026916,0.02927658,0.00005806298,0.00006555818,0.00005939402,0.0004740819,0.8607525,0.0001938947,0.06411295,0.04206416,0.0003534424],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08800251,0.000008435151,0.9102129,0.0007210316,0.0004123276,0.00009069549,0.000006481854,0.00006445395,0.0004811851],"genre_scores_gemma":[0.7310312,0.00002711241,0.2665849,0.0002235128,0.0003264434,3.401553e-7,0.00006646399,0.00001222029,0.001727809],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6436279,"threshold_uncertainty_score":0.3751117,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01758062281630666,"score_gpt":0.2240018861337144,"score_spread":0.2064212633174078,"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."}}