{"id":"W4388144635","doi":"10.2139/ssrn.4619701","title":"Sliding into Safety Net Participation: A Unified Analysis Across Multiple Programs","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Safety net; Computer science; Econometrics; Mathematics; Political science; Law","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":[0.01379886,0.0007364359,0.002882187,0.00242574,0.001308656,0.005506101,0.003581371,0.00218649,0.02650006],"category_scores_gemma":[0.03850614,0.0005170733,0.003054658,0.003481887,0.001682768,0.005660434,0.005142014,0.003299664,0.0009140209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002225027,"about_ca_system_score_gemma":0.003764276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02646299,"about_ca_topic_score_gemma":0.02143856,"domain_scores_codex":[0.989949,0.004360351,0.0003741472,0.001233674,0.001175882,0.002907054],"domain_scores_gemma":[0.9578315,0.02838436,0.004855562,0.001886002,0.002620039,0.004422495],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.006330401,0.002810046,0.6360815,0.0007503824,0.006136276,0.0009531371,0.004057956,0.1052442,0.001421741,0.08680867,0.009715348,0.1396904],"study_design_scores_gemma":[0.0005713498,0.006294022,0.5851138,0.0004203412,0.005932684,0.0002135427,0.01972731,0.299283,0.001511652,0.06758163,0.01316677,0.0001838069],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9677412,0.0008287168,0.01428401,0.001993526,0.0001000853,0.000460443,0.001929536,0.00011217,0.01255026],"genre_scores_gemma":[0.9913145,0.0001123282,0.001219952,0.0001362271,0.00006286045,0.0001493688,0.0005670124,0.00003552551,0.006402302],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02650006,"threshold_uncertainty_score":0.0886516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05677403082105961,"score_gpt":0.320499896934324,"score_spread":0.2637258661132644,"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."}}