{"id":"W4392962422","doi":"10.1007/s40300-024-00270-x","title":"Foreword to the special issue on “Survey Methods for Statistical Data Integration and New Data Sources: tools and real data applications for official statistics”","year":2024,"lang":"en","type":"article","venue":"METRON","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Statistics Canada","funders":"","keywords":"Data science; Computer science; Official statistics; Statistics; Data mining; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00562638,0.002250385,0.003350792,0.004693043,0.002020953,0.006859657,0.002333843,0.006449712,0.07045253],"category_scores_gemma":[0.02725453,0.0008264368,0.001937533,0.003158579,0.001518971,0.005143146,0.002242455,0.01059104,0.07266036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00204377,"about_ca_system_score_gemma":0.00297278,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001845168,"about_ca_topic_score_gemma":0.004120956,"domain_scores_codex":[0.9956801,0.001080911,0.0004451629,0.0005077655,0.002090952,0.0001951299],"domain_scores_gemma":[0.9721866,0.01207902,0.001630204,0.001268523,0.01083416,0.002001512],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005989985,0.000004078984,0.00001045279,0.00004265064,0.000004358542,0.000005865983,0.000002523821,0.00001129493,0.00002442717,0.0005722275,0.9962814,0.003034692],"study_design_scores_gemma":[0.000013528,0.00001827878,0.0003256347,0.0002223344,0.0000187599,0.00005474175,0.00001859009,0.000266759,0.0001050366,0.005649616,0.9932892,0.00001748986],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00005861203,0.008636911,0.004078755,0.06826025,0.9109387,0.00004271381,0.0005152699,0.0002880133,0.00718079],"genre_scores_gemma":[0.0008694952,0.007487429,0.002027309,0.04655657,0.8608094,0.0001316659,0.0009024438,0.0009419397,0.08027375],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.07045253,"threshold_uncertainty_score":0.2356873,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4188720226164224,"score_gpt":0.5374797152344185,"score_spread":0.1186076926179961,"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."}}