{"id":"W3005360994","doi":"10.1051/epjap/2020190360","title":"Advanced materials for energy harvesting, storage, sensing and environmental engineering","year":2019,"lang":"en","type":"article","venue":"The European Physical Journal Applied Physics","topic":"Gas Sensing Nanomaterials and Sensors","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Energy storage; Environmental science; Energy harvesting; Process engineering; Computer science; Energy (signal processing); Engineering; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000716213,0.0007798586,0.0007016567,0.0009688101,0.0005578447,0.001789514,0.000634289,0.002186482,0.03618927],"category_scores_gemma":[0.0006419384,0.0002172909,0.0004021571,0.0007533823,0.0004982527,0.002276683,0.001353563,0.001852006,0.01058976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005085912,"about_ca_system_score_gemma":0.000374883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001210578,"about_ca_topic_score_gemma":0.0002645999,"domain_scores_codex":[0.9997428,0.00002784373,0.00001244892,0.00006409394,0.0001119086,0.00004094387],"domain_scores_gemma":[0.9996403,0.0001223221,0.00002491036,0.0000204361,0.0001272988,0.00006466681],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002230701,0.0002687549,0.0005021936,0.003292996,0.00004508198,0.0002930798,0.0003306275,0.001149709,0.1403755,0.1926713,0.2235275,0.4373202],"study_design_scores_gemma":[0.00002150806,0.0001459993,0.0006608394,0.000292474,0.00001417198,0.0003404975,0.0001020633,0.001161951,0.01278063,0.03372088,0.950733,0.00002593232],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02026635,0.4150663,0.03151922,0.03987372,0.03875553,0.0002509887,0.0007181175,0.0006840967,0.4528655],"genre_scores_gemma":[0.1139265,0.2508185,0.02378587,0.00542582,0.02885608,0.0002765525,0.0008729788,0.0003631592,0.5756745],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03618927,"threshold_uncertainty_score":0.1210651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005076140540841506,"score_gpt":0.1652441531086832,"score_spread":0.1601680125678417,"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."}}