{"id":"W6929528383","doi":"10.5255/ukda-sn-7904-3","title":"Labour Force Survey Two-Quarter Longitudinal Dataset, July - December, 2015","year":2017,"lang":"en","type":"dataset","venue":"UK Data Archive","topic":"Information Retrieval and Search Behavior","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Unemployment; Sample (material); Current Population Survey; Population; Survey data collection; Work (physics); Data collection; Survey sampling","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","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["open_science"],"category_scores_codex":[0.001977906,0.0005632779,0.0005990795,0.0003536551,0.0006826259,0.001648355,0.01577898,0.0001865518,0.0003177382],"category_scores_gemma":[0.000620635,0.0004883435,0.00008836229,0.0002291157,0.000267802,0.002829253,0.009010644,0.001119072,0.007447212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004794479,"about_ca_system_score_gemma":0.0006610276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005530391,"about_ca_topic_score_gemma":0.01054496,"domain_scores_codex":[0.9955672,0.0003966924,0.000691288,0.001272851,0.00117543,0.0008965316],"domain_scores_gemma":[0.9874977,0.0004995323,0.0006219862,0.01072994,0.0002025529,0.0004483073],"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":[0.00003968303,0.00006378067,0.0001098454,0.00006001899,0.00005840464,0.0001376006,0.00002558645,0.000001802314,0.000001091406,0.0001728454,0.9985741,0.0007552202],"study_design_scores_gemma":[0.0006325847,0.0001100134,0.007444764,0.00006551074,0.00004612678,0.00008001021,0.000003080521,0.001157206,0.000003664177,0.0002379894,0.9896019,0.0006171164],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000007679782,0.00005859787,0.02152722,0.000161352,0.0008870633,0.0004660463,0.9766086,0.00005356486,0.0002299194],"genre_scores_gemma":[0.00003422033,0.0001472876,0.00367536,0.0004180151,0.000290486,0.00002409697,0.9948203,0.00001584908,0.0005744022],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01821172,"threshold_uncertainty_score":0.9997568,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08180976670956557,"score_gpt":0.3744456711325784,"score_spread":0.2926359044230128,"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."}}