{"id":"W2788138713","doi":"10.23889/ijpds.v3i1.415","title":"Position Statement on Population Data Science:","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Statistics Canada; University of Calgary; Manitoba Health; University of British Columbia","funders":"Economic and Social Research Council; Medical Research Council","keywords":"Data science; Population; Field (mathematics); Computer science; Discipline; Analytics; Public engagement; Informatics; Big data; Engineering ethics; Knowledge management; Sociology; Public relations; Political science; Data mining; Social science; Engineering","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.006559669,0.0001713873,0.0001187601,0.000397138,0.001709846,0.0006451153,0.004626764,0.00004052124,0.0007364811],"category_scores_gemma":[0.001380109,0.0001591172,0.0000253559,0.0006745627,0.0009324473,0.01105534,0.001993351,0.0002074831,0.0003550637],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00176305,"about_ca_system_score_gemma":0.0001562066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008531043,"about_ca_topic_score_gemma":0.000265125,"domain_scores_codex":[0.9945631,0.00006524516,0.0006362876,0.001268603,0.002933238,0.0005335112],"domain_scores_gemma":[0.9975917,0.00008462517,0.0005071551,0.001331937,0.0001855457,0.0002990901],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005048343,0.0008124409,0.4597442,0.00001411855,0.00006348037,0.00003070469,0.0008559135,0.006453455,0.06027175,0.01045552,0.01792182,0.4428718],"study_design_scores_gemma":[0.0005810306,0.0001995744,0.8395335,0.00006246386,0.00001604714,0.00005798534,0.0000814346,0.1343368,0.0007109914,0.002817474,0.02132929,0.0002733425],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9550053,0.000006161021,0.03321651,0.003756674,0.004302535,0.0006857617,0.0008130869,0.00004989795,0.002164028],"genre_scores_gemma":[0.9850699,0.00002941303,0.01174429,0.001102115,0.0006721485,0.000006965482,0.001269764,0.00001573916,0.00008961641],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4425984,"threshold_uncertainty_score":0.9995898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09722525678110634,"score_gpt":0.4376056193179299,"score_spread":0.3403803625368236,"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."}}