{"id":"W2915840056","doi":"10.2172/1135714","title":"ARRA Material Handling Equipment Composite Data Products: Data Through Quarter 4 of 2013 [Slides]","year":2014,"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; Forensic engineering; Waste management; Process engineering; Computer science; Engineering; Materials science; Composite material; History","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":[0.00191102,0.0009756037,0.0005911455,0.005398393,0.00119227,0.002432496,0.001527148,0.0005390001,0.07022396],"category_scores_gemma":[0.00533153,0.0006984905,0.0007230572,0.008725631,0.0002576367,0.001962804,0.0008582114,0.001197751,0.04850984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003453976,"about_ca_system_score_gemma":0.01085076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1561319,"about_ca_topic_score_gemma":0.1839177,"domain_scores_codex":[0.995394,0.0001642029,0.0002129808,0.000211221,0.003759942,0.00025761],"domain_scores_gemma":[0.9915817,0.000416951,0.0006849093,0.0002969069,0.006808297,0.0002111657],"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":[0.0001403183,0.00009535156,0.002673638,0.0002073881,0.00001761137,0.00001655183,0.00002792814,0.0003190578,0.0004305049,0.0005823674,0.976571,0.0189183],"study_design_scores_gemma":[0.0000374921,0.0001054868,0.0566304,0.0001581161,0.0000433762,0.00004417527,0.0002430729,0.0006089461,0.004431369,0.0004602514,0.9371879,0.00004950269],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.005559866,0.0004422661,0.001217268,0.0006351235,0.0003668001,0.0004197514,0.86551,0.001368914,0.12448],"genre_scores_gemma":[0.0132746,0.001306448,0.003423516,0.0002544367,0.00009631114,0.0007045719,0.840759,0.0006072191,0.1395739],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1561319,"threshold_uncertainty_score":0.3104463,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1001110733024979,"score_gpt":0.3274184274155407,"score_spread":0.2273073541130428,"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."}}