{"id":"W7162348032","doi":"","title":"Ανισότητα και ποσοστά θνησιμότητας στις αναπτυσσόμενες χώρες","year":2020,"lang":"en","type":"other","venue":"Νημερτής","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Phenomenon; Developing country; Inequality; Social inequality; Sample (material); Welfare; Welfare state; Developed country","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":[0.002329742,0.0002374222,0.0002810476,0.002044703,0.0009433451,0.001821063,0.0004654209,0.000401772,0.02926799],"category_scores_gemma":[0.00853494,0.0001671874,0.0002496887,0.003179922,0.001254823,0.001511804,0.0008584133,0.0008017951,0.003144143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001179197,"about_ca_system_score_gemma":0.001099306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007916049,"about_ca_topic_score_gemma":0.01582756,"domain_scores_codex":[0.9983693,0.0005938816,0.0001082026,0.0002096476,0.0004932235,0.0002257868],"domain_scores_gemma":[0.9930955,0.00425808,0.001361526,0.0004343619,0.0006413088,0.0002092535],"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":[0.0003973966,0.0004550343,0.2658472,0.001880052,0.0001747417,0.0007822118,0.03164441,0.002247477,0.004027099,0.190423,0.03296392,0.4691575],"study_design_scores_gemma":[0.00003697804,0.0001662788,0.5226395,0.00106085,0.0001049906,0.0005653497,0.02668678,0.001083382,0.003586518,0.05438232,0.389598,0.00008914091],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5303376,0.01028445,0.02947327,0.009566726,0.0005361068,0.0003042475,0.008778419,0.0001290918,0.4105901],"genre_scores_gemma":[0.9554082,0.005017862,0.008886417,0.0005550735,0.0001672865,0.0002009,0.001342261,0.00005383413,0.02836818],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02926799,"threshold_uncertainty_score":0.09791118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01478038632980197,"score_gpt":0.2414022107139366,"score_spread":0.2266218243841346,"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."}}