{"id":"W6911315720","doi":"10.5255/ukda-sn-7728-6","title":"Labour Force Survey Two-Quarter Longitudinal Dataset, October 2014 - March 2015","year":2020,"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":[0.002295759,0.001004539,0.001291217,0.002374459,0.0009022515,0.001385138,0.001878366,0.001214783,0.05562896],"category_scores_gemma":[0.0135997,0.0006715716,0.0008413987,0.005225719,0.000217873,0.001139616,0.001529501,0.001472926,0.05162058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002105241,"about_ca_system_score_gemma":0.004114753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1404716,"about_ca_topic_score_gemma":0.1667728,"domain_scores_codex":[0.9980018,0.000386259,0.0003633869,0.0003699481,0.0005396184,0.0003390535],"domain_scores_gemma":[0.9955469,0.0004388486,0.0005337553,0.000328477,0.002888115,0.0002638146],"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":[0.0001066637,0.0000330215,0.006226528,0.000415774,0.00004275073,0.00002235449,0.00007377645,0.0001413888,0.00002347073,0.0003953546,0.9877016,0.004817355],"study_design_scores_gemma":[0.0009672516,0.0001685903,0.1929608,0.001259454,0.0001678027,0.0001215681,0.001009025,0.0006315877,0.0001432072,0.001063272,0.80143,0.00007739758],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001066206,0.0001653922,0.0001304925,0.000238481,0.00008103212,0.000125397,0.9961212,0.00006817084,0.002003564],"genre_scores_gemma":[0.005019492,0.000305327,0.0003553782,0.0003444568,0.00007855293,0.001399457,0.9841647,0.00004342608,0.008289275],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1404716,"threshold_uncertainty_score":0.2793079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06991510829033552,"score_gpt":0.3497777570276703,"score_spread":0.2798626487373347,"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."}}