{"id":"W6948475902","doi":"10.5255/ukda-sn-8408-3","title":"Labour Force Survey Two-Quarter Longitudinal Dataset, April - September, 2018","year":2020,"lang":"en","type":"dataset","venue":"UK Data Archive","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","open_science","insufficient_payload"],"consensus_categories":["open_science"],"category_scores_codex":[0.000840669,0.0007352064,0.0008118904,0.0002412397,0.0002511368,0.0005665602,0.01169003,0.0001774756,0.0002167655],"category_scores_gemma":[0.0005860921,0.0006868212,0.0001063845,0.0006355302,0.0002343361,0.001845686,0.01109843,0.001218949,0.002857069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005072513,"about_ca_system_score_gemma":0.0002977735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00149422,"about_ca_topic_score_gemma":0.002077306,"domain_scores_codex":[0.9948661,0.0004938678,0.0007000934,0.002373756,0.0007618453,0.0008043346],"domain_scores_gemma":[0.9901058,0.0007772559,0.0004918668,0.008130064,0.00009276434,0.0004022602],"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":[0.0000424354,0.00005690245,0.00003420992,0.0000954089,0.00009640021,0.0003014454,0.00001052535,8.691055e-7,0.00001349299,0.0001584455,0.9976583,0.001531601],"study_design_scores_gemma":[0.0003742252,0.0002164958,0.0005004127,0.0000973624,0.00005489523,0.00006557736,0.000003020711,0.0005149868,0.0001062852,0.002109993,0.9951646,0.0007921],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[1.762331e-7,0.000130892,0.4007609,0.00009574613,0.0002635944,0.0003126509,0.598208,0.0001421587,0.00008585709],"genre_scores_gemma":[0.000007702924,0.0005902843,0.05129246,0.001515242,0.000481373,0.00002514687,0.9459183,0.00003500183,0.0001344453],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3494685,"threshold_uncertainty_score":0.9995583,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06690039269844905,"score_gpt":0.3435660369721135,"score_spread":0.2766656442736645,"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."}}