{"id":"W7095072146","doi":"","title":"Laurentian University LIQUIDITY COST DETERMINANTS FOR S&amp;amp;P 500 INDEX FUNDS ADDING STOCKS","year":2005,"lang":"en","type":"article","venue":"","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Index (typography); Market liquidity; Stock market index; Index fund","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":[0.0001408835,0.0001328194,0.0001485222,0.00009896352,0.0001898299,0.0002239101,0.0008807318,0.00008378066,0.0001618804],"category_scores_gemma":[0.00002072375,0.0001358791,0.00008198331,0.0001624514,0.00004167026,0.002001339,0.0004194786,0.00007928092,0.0002755938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008831451,"about_ca_system_score_gemma":0.00008376432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005722249,"about_ca_topic_score_gemma":0.003309822,"domain_scores_codex":[0.9989966,0.00001571775,0.0001492381,0.0003933226,0.0001013793,0.0003437121],"domain_scores_gemma":[0.9990855,0.00006274774,0.00007094997,0.000542331,0.00005636498,0.0001821484],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007739357,0.0002826732,0.01012486,0.00003839235,0.00004298167,0.000008603375,0.0004073533,0.0001575234,0.00007648506,0.0225832,0.1704195,0.7957811],"study_design_scores_gemma":[0.0004515201,0.00002752031,0.001065117,0.00001045469,0.000004607423,0.000007768655,0.00002065009,0.01031491,0.0001949829,0.0001823951,0.9874988,0.000221297],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04320536,0.0000243254,0.9342551,0.0004002355,0.000261172,0.0003050898,0.0001280531,0.0002087652,0.02121194],"genre_scores_gemma":[0.9531982,0.000007020384,0.03729929,0.0004521241,0.000120393,0.000005032182,0.00005779601,0.000007901648,0.008852257],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9099928,"threshold_uncertainty_score":0.5540987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06195123328532755,"score_gpt":0.2763307571334859,"score_spread":0.2143795238481583,"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."}}