{"id":"W6948577359","doi":"10.5255/ukda-sn-8564-1","title":"Labour Force Survey Two-Quarter Longitudinal Dataset, January - June, 2019","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":[0.002022545,0.0009578956,0.001221808,0.002385615,0.0008921726,0.001402116,0.001760393,0.001295592,0.0574108],"category_scores_gemma":[0.01101721,0.0006589693,0.0007428844,0.006365911,0.0001746887,0.001057553,0.001393152,0.001598908,0.06125433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00218849,"about_ca_system_score_gemma":0.00412202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1579616,"about_ca_topic_score_gemma":0.1958991,"domain_scores_codex":[0.9981871,0.000313093,0.0003339889,0.0003338322,0.000479634,0.0003522042],"domain_scores_gemma":[0.9957439,0.0004160304,0.0004689083,0.0003557214,0.00272069,0.0002947903],"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":[0.0001333268,0.00003509239,0.006815885,0.0004299659,0.00003925944,0.00002555515,0.00005898527,0.000111634,0.00003902732,0.0003115914,0.9870492,0.004950657],"study_design_scores_gemma":[0.0009873066,0.0001697545,0.2221611,0.0009746494,0.0001271028,0.0001128769,0.0007670621,0.0005662494,0.0001500915,0.0006966349,0.7732192,0.00006803886],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000796738,0.0001236825,0.00008384073,0.0002182704,0.00006398591,0.00009374478,0.9966244,0.00004991908,0.001945554],"genre_scores_gemma":[0.003591365,0.0002239278,0.0002375722,0.0002887314,0.00005522483,0.001085751,0.9868563,0.00003597331,0.007625179],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1579616,"threshold_uncertainty_score":0.3140844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0569528982037996,"score_gpt":0.324751783055676,"score_spread":0.2677988848518764,"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."}}