{"id":"W127359611","doi":"","title":"The use of administrative data in the edit and imputation process, tabled in Ottawa 2005","year":2006,"lang":"en","type":"book-chapter","venue":"ePrints Soton (University of Southampton)","topic":"Census and Population Estimation","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Imputation (statistics); Computer science; Database; Missing data","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":[0.0006279846,0.0001521475,0.0002689085,0.0001260078,0.000102832,0.00001976898,0.0003665769,0.00016824,0.0001087232],"category_scores_gemma":[0.0001325298,0.0001292126,0.00003980959,0.00006439223,0.0001970891,0.0002591972,0.0001276893,0.0002455698,0.00000510408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000414727,"about_ca_system_score_gemma":0.00009689195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006049232,"about_ca_topic_score_gemma":0.00724856,"domain_scores_codex":[0.9989572,0.00005458118,0.0003175463,0.0002517145,0.0002961057,0.0001229183],"domain_scores_gemma":[0.9982327,0.0005340538,0.0006183399,0.0004889779,0.0001035084,0.00002241353],"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":[0.00112491,0.00104239,0.07542177,0.002908684,0.0005411091,0.0001348706,0.07341558,0.002806121,0.00004320628,0.7613894,0.04041492,0.04075703],"study_design_scores_gemma":[0.005396586,0.0002236351,0.257745,0.00235399,0.0005922692,0.00003131442,0.01282882,0.05550414,0.00002991967,0.4861391,0.1775999,0.001555381],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7308708,0.0003624859,0.01902506,0.003851972,0.0005026515,0.008256917,0.003519504,0.0001296507,0.2334809],"genre_scores_gemma":[0.9420138,0.0001590786,0.007531374,0.00002428127,0.00008329081,0.000001936014,0.001003764,0.00004365943,0.04913879],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2752503,"threshold_uncertainty_score":0.5269135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1421023687638452,"score_gpt":0.3142060688555984,"score_spread":0.1721037000917532,"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."}}