{"id":"W7126713011","doi":"","title":"U.S. Energy and Employment Report - 2018","year":2016,"lang":"en","type":"report","venue":"eCommons (Cornell University)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Workforce; Energy (signal processing); Distribution (mathematics); Electric energy; Energy sector; Power (physics); Electric power","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":[0.001361625,0.001097134,0.0005828375,0.00503032,0.001278926,0.00206449,0.001274614,0.001005206,0.03541273],"category_scores_gemma":[0.004572115,0.0004872069,0.0004710307,0.007814784,0.0002103381,0.002074569,0.001354809,0.001208498,0.03737009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003106194,"about_ca_system_score_gemma":0.008175717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1028521,"about_ca_topic_score_gemma":0.1518245,"domain_scores_codex":[0.9977055,0.0001065908,0.0001856754,0.0001728443,0.001554412,0.0002750033],"domain_scores_gemma":[0.9963664,0.0003381713,0.0003536729,0.0001917146,0.002521405,0.0002286733],"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":[0.00007489271,0.0001527676,0.008549176,0.0002230359,0.00001521636,0.0000722749,0.00008588957,0.000177695,0.000185401,0.002037694,0.9737829,0.0146431],"study_design_scores_gemma":[0.00003019193,0.00003518246,0.04305468,0.0003264057,0.00002138161,0.00005591141,0.000481843,0.0001852532,0.0007460205,0.000479457,0.9545563,0.00002739286],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.005934208,0.000900786,0.0004172128,0.001480799,0.0007307342,0.000322078,0.9131858,0.0004133763,0.07661499],"genre_scores_gemma":[0.01826462,0.004349129,0.001941258,0.001375975,0.0003862497,0.001959285,0.7735861,0.0003025807,0.1978348],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1028521,"threshold_uncertainty_score":0.2045068,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0562388416516244,"score_gpt":0.2284912673813582,"score_spread":0.1722524257297338,"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."}}