{"id":"W7097587232","doi":"","title":"49 In Search of Data Beyond Traditional Measures","year":2008,"lang":"en","type":"article","venue":"","topic":"Census and Population Estimation","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Data collection; Public policy; Constant (computer programming); E-Government","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002492561,0.00003286503,0.00007425559,0.00005525578,0.00002335947,0.000001859372,0.00009653963,0.00002326139,0.000337487],"category_scores_gemma":[0.00008961668,0.0000286358,0.00001128244,0.00008740488,0.00002468521,0.0001321418,0.00002057193,0.00004093197,0.000009993747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000103093,"about_ca_system_score_gemma":0.00003154215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006832553,"about_ca_topic_score_gemma":0.0001261502,"domain_scores_codex":[0.9994512,0.00002353895,0.0001734175,0.00007697209,0.0002184527,0.00005642663],"domain_scores_gemma":[0.9995793,0.0001373983,0.00002593495,0.0002016569,0.00003877188,0.00001691847],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00003097049,0.0005362116,0.09168683,0.0001068365,0.00002084873,0.000008413446,0.001471049,0.0002987818,0.0008001543,0.8639455,0.03515936,0.005935083],"study_design_scores_gemma":[0.00109829,0.00004657426,0.6562806,0.00004088597,0.00001315474,0.00005792998,0.0001002284,0.04408801,0.001678194,0.2948321,0.001561713,0.0002023173],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9407299,0.00002601743,0.007609291,0.0004590255,0.00003753826,0.0001431305,0.00009416042,0.00002550748,0.05087543],"genre_scores_gemma":[0.9777207,0.000006186498,0.02184372,0.00001867223,0.00002502819,0.000001058972,0.00013405,0.000003873939,0.0002467591],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5691133,"threshold_uncertainty_score":0.3695246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4807940352436562,"score_gpt":0.3973204006929013,"score_spread":0.08347363455075485,"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."}}