{"id":"W7097785127","doi":"","title":"PROVIDING GREATER ACCESSIBILITY TO SURVEY DATA FOR ANALYSIS","year":2001,"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":"Microdata (statistics); Confidentiality; Public use; Census; Documentation; Survey data collection; Data quality; Permission; Data collection","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":[0.001081467,0.00006088695,0.0001431806,0.00008405931,0.00006179004,0.00004723106,0.0001885529,0.00002760124,0.0003308712],"category_scores_gemma":[0.001035541,0.0000466141,0.00003589315,0.0004309936,0.000003805611,0.000182383,0.00008186657,0.00001719343,0.000009973051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002125626,"about_ca_system_score_gemma":0.000009765768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003244488,"about_ca_topic_score_gemma":0.003891126,"domain_scores_codex":[0.9992974,0.00004213318,0.0002206372,0.0002359211,0.00009535903,0.0001085935],"domain_scores_gemma":[0.9988237,0.000276683,0.00005431512,0.0006930322,0.0001066289,0.00004562673],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003277213,0.00003396747,0.9913988,0.00002044529,0.00007437827,1.577933e-7,0.00008533265,0.00007239074,0.00001017473,0.001055456,0.004415923,0.002800211],"study_design_scores_gemma":[0.000136934,0.00001101512,0.8839186,0.000002909688,0.0001716389,3.597594e-7,0.00001027654,0.109435,0.0000526762,0.005215744,0.0009464478,0.00009845039],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5426041,8.770761e-7,0.4560557,0.0001747179,0.000027918,0.0002901381,0.0001092793,0.00004286172,0.0006943735],"genre_scores_gemma":[0.9479548,2.562728e-7,0.05001327,0.0000732371,0.00002987675,0.00001181812,0.000631482,0.00000652595,0.00127869],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4060425,"threshold_uncertainty_score":0.3622808,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4684211264334238,"score_gpt":0.4783435086842976,"score_spread":0.009922382250873885,"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."}}