{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001431875,0.0004132156,0.0006270337,0.00005372905,0.00009195905,0.0001877529,0.003649629,0.000209986,0.005382914],"category_scores_gemma":[0.00005181484,0.0003216785,0.00004467825,0.0001442952,0.0002172394,0.00107148,0.008046879,0.0002297034,0.0005034218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001453349,"about_ca_system_score_gemma":0.00005232754,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01864626,"about_ca_topic_score_gemma":0.0001107359,"domain_scores_codex":[0.9958384,0.00007845587,0.0009039386,0.001495948,0.001265345,0.000417936],"domain_scores_gemma":[0.9934425,0.00002859849,0.0006190168,0.005809494,0.00004053162,0.00005988779],"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":[0.000009084591,0.0001236299,0.0005869168,0.0002925164,0.0000931153,0.000004846996,0.00004532434,0.00001681089,0.002284189,0.000005746097,0.9889746,0.007563258],"study_design_scores_gemma":[0.0001528867,0.00009162559,0.0004421366,0.0003604867,0.0001824254,0.00001211372,0.00005854168,0.00089393,0.005002484,0.0001909569,0.9920456,0.0005668082],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.01604828,0.0008520656,0.01540623,0.003095602,0.006978834,0.005417204,0.00310458,0.001039142,0.9480581],"genre_scores_gemma":[0.1994108,0.03197528,0.480132,0.0008867702,0.006170785,0.0003573214,0.1011638,0.000636247,0.179267],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7687911,"threshold_uncertainty_score":0.9999759,"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."}}