{"id":"W4409031944","doi":"10.1177/11786329251330032","title":"Understanding Unmet Healthcare Needs in Nigeria: Implications for Universal Health Coverage","year":2025,"lang":"en","type":"article","venue":"Health Services Insights","topic":"Healthcare Systems and Reforms","field":"Economics, Econometrics and Finance","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Nigerians; Health care; Medicine; Logistic regression; Environmental health; Population; Inequality; Cross-sectional study; Economic growth","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008933516,0.0002341422,0.0008494147,0.001112217,0.0006994583,0.0000677935,0.000302199,0.0002207495,0.00000971133],"category_scores_gemma":[0.000008250014,0.0002348532,0.000110752,0.001355591,0.00003186981,0.0002903798,0.00006414703,0.000266235,0.0000241752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002931366,"about_ca_system_score_gemma":0.0007853093,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02511654,"about_ca_topic_score_gemma":0.03618979,"domain_scores_codex":[0.9970632,0.00007911677,0.001477461,0.000536482,0.00004668341,0.0007970227],"domain_scores_gemma":[0.9983641,0.00006978936,0.000683943,0.00050279,0.00005715563,0.0003222078],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003033354,0.00007997607,0.04063628,0.004235032,0.0000285515,6.43688e-7,0.008613147,0.00006023791,6.51267e-7,0.9442456,0.0005961438,0.001473387],"study_design_scores_gemma":[0.003219019,0.0005712984,0.1504208,0.001581158,0.000001767356,0.000005620742,0.01299724,0.001229332,0.000002461227,0.4294816,0.3998697,0.0006199919],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1906296,0.08736365,0.1680439,0.4925716,0.00965314,0.01305367,0.002908786,0.000673068,0.03510259],"genre_scores_gemma":[0.9789949,0.002990337,0.0002888681,0.01675946,0.0001226382,0.0001235504,0.0001670865,0.00003247184,0.0005206562],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7883653,"threshold_uncertainty_score":0.9813972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08570683555588633,"score_gpt":0.310167422523531,"score_spread":0.2244605869676447,"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."}}