{"id":"W1980831228","doi":"10.3152/147154302781780822","title":"Do US Congressional earmarks increase research output at universities?","year":2002,"lang":"en","type":"article","venue":"Science and Public Policy","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Appropriation; Competition (biology); Instrumental variable; Quality (philosophy); Estimation; Political science; Public economics; Economics; Public administration; Business; Management; Econometrics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["metaresearch","bibliometrics"],"domain":"incentives","study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["metaresearch","bibliometrics"],"domain":"incentives","study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.01660823,0.0004496681,0.001145361,0.00515092,0.001913117,0.01076844,0.00106084,0.003440846,0.01631548],"category_scores_gemma":[0.1314332,0.0003817491,0.0007638246,0.01460133,0.002837114,0.00621213,0.003094774,0.001569662,0.002238705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004940448,"about_ca_system_score_gemma":0.004192325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005933406,"about_ca_topic_score_gemma":0.00862192,"domain_scores_codex":[0.9875244,0.004260525,0.0008715984,0.0009109363,0.004394521,0.002037958],"domain_scores_gemma":[0.8191475,0.08670145,0.06761457,0.006742403,0.01314236,0.006651814],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007332144,0.0009534424,0.6932101,0.001003878,0.0007198272,0.0006669986,0.003474557,0.003250268,0.001822953,0.04823371,0.03072958,0.2152014],"study_design_scores_gemma":[0.0001391246,0.0003629215,0.9164271,0.000306654,0.0002656176,0.0001333463,0.003664558,0.0008639865,0.00232225,0.02046185,0.05498673,0.00006579194],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7233528,0.0152449,0.001587362,0.08802305,0.0009417249,0.00009982924,0.002006514,0.0004911832,0.1682526],"genre_scores_gemma":[0.9812647,0.00446582,0.0005993863,0.004354445,0.001035606,0.00007514308,0.0004964533,0.00005485226,0.007653645],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9948491,"threshold_uncertainty_score":0.08783382,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6548266178634141,"score_gpt":0.590624394806003,"score_spread":0.06420222305741108,"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."}}