{"id":"W6967408704","doi":"10.5255/ukda-sn-5389-1","title":"Quarterly Labour Force Survey, March - May, 2005: Local Area Data","year":2006,"lang":"en","type":"dataset","venue":"UK Data Archive","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Welsh; Quarter (Canadian coin); Seasonal adjustment; Seasonality; Local authority; Data series","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002616418,0.0008552472,0.0011574,0.003887973,0.0007310225,0.001593272,0.001491431,0.0007982817,0.03696445],"category_scores_gemma":[0.009839277,0.0005927224,0.000525374,0.01021907,0.0001872076,0.001169529,0.0009764628,0.001527662,0.0479807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002643287,"about_ca_system_score_gemma":0.004063216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1304334,"about_ca_topic_score_gemma":0.1285833,"domain_scores_codex":[0.997348,0.0004161965,0.0004948106,0.0004454107,0.0009731671,0.0003224336],"domain_scores_gemma":[0.9941221,0.0005818682,0.0007781473,0.0004020237,0.00378014,0.0003356685],"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":[0.00006942541,0.00004280142,0.01009916,0.0003913297,0.00002971694,0.00001975051,0.0001993046,0.000133655,0.00003014427,0.0004564222,0.9769819,0.01154641],"study_design_scores_gemma":[0.0001323322,0.00008508705,0.2803639,0.0005928367,0.00004875563,0.000064074,0.000893175,0.0002489915,0.0000943608,0.0003490437,0.717086,0.00004141863],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00259445,0.000356274,0.00024237,0.0004236235,0.0001663176,0.0003037033,0.986989,0.0001458881,0.008778277],"genre_scores_gemma":[0.01104514,0.0009277122,0.0009941937,0.0005584362,0.0001236082,0.001550573,0.9675733,0.00007404108,0.01715311],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1304334,"threshold_uncertainty_score":0.2593485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06799948662267313,"score_gpt":0.32070060158556,"score_spread":0.2527011149628868,"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."}}