{"id":"W4408152241","doi":"10.69611/cahiers19-1-13","title":"ECONOMIC GROWTH AND ITS IMPACT ON THE CONGOLESE POPULATION","year":2021,"lang":"en","type":"article","venue":"˜Les œCahiers du CEDIMES.","topic":"Economic Growth and Development","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Francophone University Association","funders":"","keywords":"Poverty reduction; Agriculture; Rural poverty; Poverty; Economics; Economic growth; Business; Development economics; Geography","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":[0.0005011972,0.0002039974,0.0001659633,0.0006984913,0.0008513774,0.001552843,0.0001745334,0.0003124329,0.004703032],"category_scores_gemma":[0.001205847,0.0000569759,0.0001520178,0.001397954,0.0008581451,0.0007421959,0.0008652621,0.0004927868,0.0002340343],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002671847,"about_ca_system_score_gemma":0.0009465768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02541711,"about_ca_topic_score_gemma":0.03820099,"domain_scores_codex":[0.999675,0.0001562335,0.000008489662,0.00002452104,0.00002773948,0.0001080034],"domain_scores_gemma":[0.9996011,0.0001073352,0.0001159547,0.00001912399,0.00008431913,0.00007214832],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006662859,0.0001808197,0.4997369,0.0007955059,0.000226852,0.006124265,0.01999287,0.003044453,0.005359227,0.2128974,0.02481555,0.2261598],"study_design_scores_gemma":[0.00001865196,0.0002131748,0.7853109,0.0006609874,0.00009674228,0.001608732,0.0253684,0.002850738,0.001279021,0.01596195,0.1665687,0.00006205586],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8951144,0.01290202,0.0006503019,0.01621804,0.0001782046,0.00001871561,0.001333705,0.00002450502,0.07356005],"genre_scores_gemma":[0.9948066,0.00264902,0.0002604232,0.0001987531,0.00003317886,0.00000665097,0.00009254461,0.000003420708,0.001949557],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02541711,"threshold_uncertainty_score":0.05053836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006987435511935754,"score_gpt":0.2078595427263038,"score_spread":0.200872107214368,"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."}}