{"id":"W2981863111","doi":"10.5539/ass.v15n11p116","title":"Demographic Issues in Malaysia","year":2019,"lang":"en","type":"article","venue":"Asian Social Science","topic":"Demographic Trends and Gender Preferences","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universiti Sains Malaysia","keywords":"Malay; Ethnic group; Fertility; Total fertility rate; Population; Demography; Birth rate; Socioeconomics; Population ageing; Geography; Family planning; Sociology; Research methodology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.000862075,0.0004708563,0.0002033089,0.001186233,0.002529554,0.002109237,0.0004017753,0.0009038575,0.02048164],"category_scores_gemma":[0.002396489,0.0001731382,0.0002925888,0.001461665,0.0009123972,0.00260121,0.002065168,0.00186207,0.003490776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001891107,"about_ca_system_score_gemma":0.003574097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01166706,"about_ca_topic_score_gemma":0.01283238,"domain_scores_codex":[0.9991096,0.0003176423,0.00007368629,0.00008169243,0.0001972109,0.0002201533],"domain_scores_gemma":[0.9989895,0.0001392404,0.0002629405,0.00003474353,0.0002446274,0.0003289528],"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":[0.00008572114,0.0002040224,0.1277516,0.001677295,0.00004313023,0.003906311,0.04740774,0.0003855817,0.0009367942,0.05998336,0.3656633,0.3919551],"study_design_scores_gemma":[0.000004967016,0.000101196,0.07456022,0.001407617,0.00001270271,0.003283262,0.03504951,0.0001087181,0.0001842867,0.004040543,0.8811952,0.00005170673],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2273819,0.09105326,0.001326574,0.1477597,0.009928551,0.0004010453,0.006174108,0.0002468828,0.5157279],"genre_scores_gemma":[0.7103415,0.1036468,0.001970338,0.03319112,0.003610374,0.0004507948,0.002811104,0.0001153245,0.1438627],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02048164,"threshold_uncertainty_score":0.06851792,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02069726262218841,"score_gpt":0.3157786569804457,"score_spread":0.2950813943582573,"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."}}