{"id":"W6892363278","doi":"10.5255/ukda-sn-8778-2","title":"Labour Force Survey Two-Quarter Longitudinal Dataset, July - December, 2020","year":2021,"lang":"en","type":"dataset","venue":"UK Data Archive","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Sample (material); Unemployment; Survey data collection; Work (physics); Data collection; Longitudinal study; Longitudinal 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002269329,0.0009923625,0.001178382,0.002318735,0.0007933231,0.001301851,0.001605016,0.001286258,0.04897164],"category_scores_gemma":[0.00964088,0.0006728262,0.0007505617,0.006149278,0.0001687412,0.001065735,0.001179464,0.001454858,0.05241589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001967859,"about_ca_system_score_gemma":0.004377899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1623106,"about_ca_topic_score_gemma":0.1762591,"domain_scores_codex":[0.9984128,0.0002521405,0.0002667987,0.0002852299,0.0004715367,0.0003113769],"domain_scores_gemma":[0.9960394,0.0003689791,0.0004015413,0.0002695257,0.002603309,0.0003171978],"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":[0.00009278504,0.00002650698,0.004860195,0.0003727157,0.00003454154,0.00002033949,0.0000363651,0.0001111004,0.00003240628,0.0002686494,0.989787,0.00435744],"study_design_scores_gemma":[0.0009114678,0.0001655029,0.2072095,0.0009179842,0.0001381467,0.0001199793,0.0005849025,0.0006510266,0.0001569759,0.0007256453,0.7883563,0.00006250975],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005539522,0.0001113614,0.00007227067,0.0001648316,0.00005199319,0.0000605577,0.9975884,0.00004433861,0.001352256],"genre_scores_gemma":[0.002565879,0.000189597,0.0002350867,0.0002428273,0.00004150108,0.0007214573,0.9909455,0.00002651147,0.005031742],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1623106,"threshold_uncertainty_score":0.3227316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05816110586283827,"score_gpt":0.3363172326043362,"score_spread":0.2781561267414979,"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."}}