{"id":"W4200159776","doi":"10.1088/1757-899x/1203/3/032032","title":"Probabilistic Modelling of Demographic Changes in Singapore’s Neighbourhoods","year":2021,"lang":"en","type":"article","venue":"IOP Conference Series Materials Science and Engineering","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Relocation; Ethnic group; Population; Geography; Neighbourhood (mathematics); Fertility; Proxy (statistics); Scale (ratio); Context (archaeology); Total fertility rate; Demographic economics; Demography; Sociology; Family planning; Economics; Research methodology; Statistics","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":[0.001014977,0.0001274106,0.0002805621,0.0001958898,0.00029631,0.0002318184,0.0001870053,0.0000599723,0.0000831225],"category_scores_gemma":[0.0005756841,0.000126485,0.00001621337,0.0009110275,0.0007229703,0.0005258481,0.00008855989,0.00006257742,8.932533e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004242032,"about_ca_system_score_gemma":0.0004059601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004850198,"about_ca_topic_score_gemma":0.00114172,"domain_scores_codex":[0.9986135,0.00004433071,0.0002554941,0.0002922138,0.0003979142,0.0003965972],"domain_scores_gemma":[0.9991848,0.00007383058,0.00007534704,0.0001348292,0.0004381063,0.00009312655],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003082898,0.00008034276,0.00286848,0.0004029427,0.00002369638,0.00002530447,0.04191456,0.008074691,0.6200264,0.3237178,0.00001063291,0.002824346],"study_design_scores_gemma":[0.001212002,0.0003501573,0.03509987,0.001680594,0.00009379917,0.00003771895,0.0506322,0.03018311,0.8524526,0.02016129,0.006032592,0.002064073],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957796,0.0002606949,0.0007898239,0.000664008,0.0004345048,0.0001264577,0.000008833972,0.00005022736,0.001885874],"genre_scores_gemma":[0.9977532,0.0009633537,0.001079982,0.00002209506,0.00006959312,0.00001767355,0.000001656088,0.000006940596,0.00008547625],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3035565,"threshold_uncertainty_score":0.515791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04388218225098003,"score_gpt":0.250236197231471,"score_spread":0.206354014980491,"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."}}