{"id":"W6976715305","doi":"10.6068/dp1513282a51427","title":"TREND: Bureau of Labor Statistics. National Compensation Survey [Archive]: Civilian Workers - Employment | Labor Metric: All workers | Industry: All workers | Occupation: Interior designers, 07/2007 - 07/2010. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 002-023-001","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Earnings; Metropolitan area; Wages and salaries; Compensation of employees; Sample (material); Incentive; Payment; Workers' compensation; Quarter (Canadian coin)","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":[0.002403155,0.001924031,0.001776957,0.005538376,0.001093796,0.002783587,0.003361096,0.001401755,0.1306916],"category_scores_gemma":[0.01922682,0.001270589,0.001242334,0.02137287,0.0003242658,0.003031923,0.001659817,0.003642093,0.1470097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003548246,"about_ca_system_score_gemma":0.007337739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1213055,"about_ca_topic_score_gemma":0.08406054,"domain_scores_codex":[0.9965116,0.0004952087,0.0006452565,0.0006908478,0.001232366,0.0004246945],"domain_scores_gemma":[0.9801975,0.001954444,0.001959553,0.00128787,0.0139169,0.0006836908],"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":[0.00002021103,0.00001290703,0.0008619303,0.0001897566,0.00001146241,0.00000344442,0.00001483282,0.00005022005,0.00001254872,0.0002688431,0.9965531,0.002000847],"study_design_scores_gemma":[0.0001537947,0.00002423665,0.01576634,0.0005745626,0.00004183613,0.00002067274,0.0002418669,0.0002068884,0.00009218616,0.0008049347,0.9820367,0.00003592919],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009208416,0.00004503739,0.00008183046,0.0001285054,0.00006502192,0.00004958206,0.9978918,0.0001071992,0.001538923],"genre_scores_gemma":[0.0005273856,0.0001475626,0.0003730285,0.0001537018,0.00003834026,0.0004554409,0.9954958,0.0001257182,0.002683107],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1306916,"threshold_uncertainty_score":0.4372069,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0910324918508126,"score_gpt":0.3523327748656283,"score_spread":0.2613002830148157,"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."}}