{"id":"W4399692197","doi":"10.2172/2371715","title":"Context-Aware Learning for Inverse Design in Photovoltaics","year":2022,"lang":"en","type":"report","venue":"","topic":"CCD and CMOS Imaging Sensors","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Renewable Energy Laboratory; Iowa State University; Advanced Research Projects Agency; Advanced Research Projects Agency - Energy; York University; U.S. Department of Energy","keywords":"Photovoltaics; Context (archaeology); Inverse; Computer science; Engineering; Geography; Photovoltaic system; Mathematics; Electrical engineering; Geometry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0007374117,0.0005206135,0.0005200191,0.0002607775,0.0003133854,0.0008775832,0.0007665411,0.000861629,0.003583391],"category_scores_gemma":[0.001307616,0.0004191783,0.0008009986,0.0002243359,0.0006248355,0.0009775199,0.001331902,0.001468948,0.0005776924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000965123,"about_ca_system_score_gemma":0.0007294547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001424263,"about_ca_topic_score_gemma":0.002016052,"domain_scores_codex":[0.9996991,0.00009890297,0.0000140443,0.00005729991,0.00009665178,0.00003394026],"domain_scores_gemma":[0.9997113,0.0001522921,0.00001928333,0.00003795482,0.00005967851,0.00001935753],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000731672,0.00006901555,0.0005521979,0.0002320564,0.00003569144,0.00007825022,0.0001165684,0.8068637,0.01058684,0.07263058,0.002773407,0.1059886],"study_design_scores_gemma":[0.00000822416,0.00004175003,0.0001057169,0.00001961631,0.000003973562,0.00002029146,0.00001631749,0.9656044,0.003291917,0.02465288,0.0062264,0.000008437612],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01690537,0.0007233156,0.9747745,0.0004623568,0.00009222554,0.00003617233,0.00006064263,0.0004332654,0.006512206],"genre_scores_gemma":[0.492628,0.00142761,0.4930516,0.0003768329,0.000105667,0.0001961672,0.000320559,0.0002256328,0.01166801],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003583391,"threshold_uncertainty_score":0.01198769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05338800572233756,"score_gpt":0.2670707419309177,"score_spread":0.2136827362085802,"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."}}