{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002482602,0.0004389758,0.0007208644,0.00005972179,0.0001046534,0.0001660819,0.003760378,0.0002204841,0.002091967],"category_scores_gemma":[0.00008486287,0.0003505391,0.00005257194,0.0001473042,0.0002257086,0.0007275456,0.007416158,0.0002422658,0.0002641733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001483902,"about_ca_system_score_gemma":0.00005155673,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01116833,"about_ca_topic_score_gemma":0.000203233,"domain_scores_codex":[0.9955105,0.0001108063,0.0009830992,0.001618562,0.001342226,0.0004348016],"domain_scores_gemma":[0.9929365,0.00004289098,0.0007025615,0.006218398,0.0000368962,0.00006273114],"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":[0.0000192328,0.0001249387,0.00105788,0.0004232501,0.0001033881,0.000006314208,0.00004668807,0.00003682207,0.002342311,0.000009898148,0.9875817,0.008247608],"study_design_scores_gemma":[0.0001683279,0.0001083707,0.0003315177,0.0004191834,0.0002071967,0.00001374942,0.00003542622,0.0009295561,0.005459078,0.0001967876,0.9915767,0.0005540776],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01464646,0.0007072379,0.06273069,0.003389122,0.008944699,0.004864866,0.003260472,0.001333718,0.9001228],"genre_scores_gemma":[0.4352102,0.01691555,0.3876832,0.0009970359,0.006576426,0.0001799962,0.08103805,0.0005776879,0.07082181],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8293009,"threshold_uncertainty_score":0.9998947,"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."}}