{"id":"W2797963898","doi":"10.5281/zenodo.1217622","title":"Icpsr Census Metadata Repository","year":2018,"lang":"en","type":"article","venue":"Deep Blue (University of Michigan)","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Public Safety Research and Treatment","funders":"","keywords":"Metadata; Census; Computer science; Metadata repository; Geospatial metadata; World Wide Web; Data science; Database; Geography; Information retrieval; Meta Data Services; Population; Demography; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004085616,0.00007014268,0.0001585894,0.0001325007,0.001192733,0.00002512514,0.0003933547,0.00007747483,0.00007017609],"category_scores_gemma":[0.0000429916,0.00008634721,0.00008305376,0.000354764,0.0008474124,0.0005630775,0.0001233366,0.00006463559,0.0001018344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002257969,"about_ca_system_score_gemma":0.0000479031,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004287433,"about_ca_topic_score_gemma":0.117627,"domain_scores_codex":[0.9991438,0.00008845735,0.0001187074,0.000136141,0.0003096672,0.0002032431],"domain_scores_gemma":[0.9991328,0.00004912386,0.0001778555,0.0002413541,0.0003238125,0.00007509365],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0000319405,0.00003528052,0.00129567,0.00002506785,0.0001829877,0.00001265375,0.957186,0.000002432053,0.0002235247,0.03899063,0.001024651,0.0009891342],"study_design_scores_gemma":[0.0002680106,0.00003335239,0.004716743,0.00001618828,0.0000470381,0.000002673721,0.681557,0.00003577101,0.000106965,0.0001749912,0.3129143,0.0001270193],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8951128,0.0001000487,0.001072459,0.0003548023,0.0004514848,0.0001244751,0.00001647728,0.00007195877,0.1026955],"genre_scores_gemma":[0.9923307,0.00003689205,0.001076054,0.00004922896,0.0001337102,1.170945e-7,0.000006775955,0.000003438911,0.006363043],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3118896,"threshold_uncertainty_score":0.9173659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01540445247018261,"score_gpt":0.2265739975964951,"score_spread":0.2111695451263125,"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."}}