{"id":"W2295407543","doi":"10.2172/1118093","title":"ARRA Material Handling Equipment Composite Data Products: Data through Quarter 2 of 2013","year":2013,"lang":"en","type":"report","venue":"","topic":"Recycling and Waste Management Techniques","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Office of Energy Efficiency; National Renewable Energy Laboratory; U.S. Department of Energy","keywords":"Quarter (Canadian coin); Composite number; Database; Waste management; Process engineering; Business; Computer science; Materials science; Engineering; Composite material","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":[0.002995121,0.001137774,0.0006889185,0.005012398,0.00119524,0.002740514,0.001521695,0.0005833149,0.03666273],"category_scores_gemma":[0.005801369,0.000688485,0.0007150205,0.007584334,0.0002846691,0.002029641,0.0009107045,0.001377235,0.03249461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003916855,"about_ca_system_score_gemma":0.01234979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1372522,"about_ca_topic_score_gemma":0.1597909,"domain_scores_codex":[0.9926196,0.0002436543,0.0002788892,0.0002994591,0.006258626,0.0002997671],"domain_scores_gemma":[0.9906874,0.0004743565,0.0006454888,0.0003826744,0.007616108,0.0001939281],"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":[0.0002957154,0.0002107477,0.005620762,0.0003933417,0.00003697932,0.00004433339,0.0000714472,0.0007210574,0.00122865,0.001200067,0.9503587,0.03981816],"study_design_scores_gemma":[0.00004536603,0.0001313501,0.04370353,0.0001618121,0.0000528402,0.00005867212,0.0003026423,0.0009070372,0.009443076,0.0005135789,0.9446288,0.00005129185],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.009682641,0.0007058928,0.002105046,0.0007136778,0.0003507982,0.0005193629,0.8638415,0.001256391,0.1208247],"genre_scores_gemma":[0.01724067,0.002006844,0.005466671,0.0002849688,0.00007723334,0.0008168494,0.8519295,0.0007000623,0.1214771],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1372522,"threshold_uncertainty_score":0.2729066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1041796136637368,"score_gpt":0.3245669185210711,"score_spread":0.2203873048573343,"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."}}