{"id":"W6928906534","doi":"10.3886/e130285v1","title":"Data and Code for: \"Money and Politics: The Effects of Campaign Spending Limits on Political Entry and Competition\"","year":2022,"lang":"en","type":"dataset","venue":"ICPSR Data Holdings","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; HEC Montréal","funders":"","keywords":"Politics; Exploit; Regression discontinuity design; Competition (biology); Code (set theory); Panel data","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001960873,0.001361522,0.001004454,0.003255568,0.0009363818,0.002476861,0.002421173,0.002519468,0.09027541],"category_scores_gemma":[0.01176312,0.0008551361,0.0008490357,0.007516345,0.00053962,0.001147964,0.001889866,0.002340824,0.07531795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002501544,"about_ca_system_score_gemma":0.003365271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1027819,"about_ca_topic_score_gemma":0.1190341,"domain_scores_codex":[0.9980325,0.0003268935,0.000313272,0.0003555157,0.000639434,0.0003322751],"domain_scores_gemma":[0.9929341,0.001797704,0.001687836,0.001062374,0.002058262,0.0004597968],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003678969,0.00003290254,0.00168823,0.0002959933,0.00001239771,0.00001794673,0.00004557752,0.0002275729,0.00004381534,0.000671799,0.995577,0.001350003],"study_design_scores_gemma":[0.0004213729,0.00002771397,0.01851752,0.00031565,0.00002384078,0.00003955219,0.0002621207,0.0004835503,0.0003079953,0.0009605734,0.9785977,0.00004243994],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001894358,0.00001785638,0.00004179349,0.0001122757,0.00001207482,0.00001963479,0.9987825,0.00008450242,0.0007399668],"genre_scores_gemma":[0.0009456567,0.00003361022,0.000270734,0.00006834028,0.000008669528,0.0002510151,0.9964271,0.00005753044,0.001937337],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1027819,"threshold_uncertainty_score":0.3020013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05951526998791216,"score_gpt":0.3296201997314821,"score_spread":0.2701049297435699,"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."}}