{"id":"W7019610922","doi":"","title":"Güney Avrupa refah rejimi bağlamında nüfusun yaşlanmasının sosyal etkileri: İspanya, İtalya, Yunanistan ve Türkiye mukayesesi","year":2020,"lang":"tr","type":"dissertation","venue":"Marmara University Open Access System","topic":"Intergenerational Family Dynamics and Caregiving","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Social policy; Quarter (Canadian coin); Population ageing; Social protection; Social life; Social assistance; Population; Pension system","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009897905,0.0007566322,0.0004492951,0.001023954,0.003923353,0.003600907,0.0005019748,0.001347403,0.02094247],"category_scores_gemma":[0.001219612,0.0003474099,0.0005242122,0.001330421,0.001977327,0.001651952,0.002868229,0.001669808,0.003440902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002470374,"about_ca_system_score_gemma":0.00515988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02800911,"about_ca_topic_score_gemma":0.05138638,"domain_scores_codex":[0.9993661,0.0001381409,0.00003134997,0.0000935448,0.0001684823,0.0002023785],"domain_scores_gemma":[0.9994222,0.00008460302,0.0001223624,0.00005548401,0.0001916742,0.000123695],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001473213,0.00055456,0.175123,0.00314403,0.0003430073,0.01288516,0.05848665,0.002318637,0.03219301,0.09965359,0.09283509,0.5209901],"study_design_scores_gemma":[0.00004212932,0.0002691651,0.1511743,0.001153546,0.0001353545,0.003522309,0.04922704,0.0006575871,0.007131297,0.00825828,0.7782986,0.0001302902],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5258277,0.02334646,0.006492435,0.02083903,0.001619941,0.0002574419,0.001323274,0.0004489095,0.4198449],"genre_scores_gemma":[0.8371922,0.01081276,0.005761451,0.002043037,0.0002835227,0.000134232,0.001241055,0.000135514,0.1423962],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02800911,"threshold_uncertainty_score":0.0700596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03797441549351145,"score_gpt":0.3335764329100512,"score_spread":0.2956020174165398,"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."}}