{"id":"W2890912884","doi":"10.23889/ijpds.v3i4.918","title":"Population Data Science: The science of data about people","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Economic and Social Research Council; Medical Research Council","keywords":"Population; Data science; Computer science; Informatics; Field (mathematics); Knowledge management; Political science; Sociology","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":[0.03644889,0.00082754,0.00167736,0.009553929,0.003110044,0.01624933,0.004062201,0.004663078,0.01404239],"category_scores_gemma":[0.08552008,0.0007363689,0.001231787,0.01615274,0.01724969,0.01794479,0.009696537,0.007600688,0.004030326],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004869316,"about_ca_system_score_gemma":0.01483504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005315409,"about_ca_topic_score_gemma":0.002745579,"domain_scores_codex":[0.9504332,0.02947784,0.002991903,0.005037774,0.0113111,0.0007481158],"domain_scores_gemma":[0.8670287,0.1028203,0.005852069,0.01166438,0.01050157,0.002133122],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004010064,0.00004658663,0.005099401,0.002834774,0.000113809,0.0002388822,0.003834295,0.001581459,0.0004096789,0.7347598,0.05939159,0.1916496],"study_design_scores_gemma":[0.00001214161,0.00004296278,0.001988168,0.003206921,0.00003793601,0.0003351836,0.002545956,0.001793301,0.0004892433,0.4918306,0.4976562,0.00006134581],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01122374,0.1098187,0.444838,0.2708011,0.01226497,0.001265133,0.01351952,0.00132939,0.1349393],"genre_scores_gemma":[0.3072653,0.188903,0.361628,0.05624894,0.02435585,0.003800987,0.01674471,0.001031468,0.04002172],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03644889,"threshold_uncertainty_score":0.1927625,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.455399970034002,"score_gpt":0.5671411276653473,"score_spread":0.1117411576313453,"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."}}