{"id":"W3010153336","doi":"10.1039/c9ee90064k","title":"Correction: A multi-objective optimization-based layer-by-layer blade-coating approach for organic solar cells: rational control of vertical stratification for high performance","year":2019,"lang":"en","type":"article","venue":"Energy & Environmental Science","topic":"Organic Electronics and Photovoltaics","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carbon Engineering (Canada)","funders":"Australian Synchrotron; Australian Nuclear Science and Technology Organisation","keywords":"Stratification (seeds); Blade (archaeology); Layer (electronics); Coating; Materials science; Engineering; Mechanical engineering; Nanotechnology; Biology","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":[0.002065735,0.003080487,0.002594813,0.00327513,0.002051254,0.003441288,0.004391054,0.004422899,0.1314868],"category_scores_gemma":[0.03522788,0.001384039,0.002465535,0.003092538,0.001402223,0.002849163,0.002000817,0.00833536,0.05017229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002724634,"about_ca_system_score_gemma":0.004187977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01186482,"about_ca_topic_score_gemma":0.01712836,"domain_scores_codex":[0.9967998,0.0003856507,0.0003867399,0.0003987757,0.001687677,0.0003412673],"domain_scores_gemma":[0.9804363,0.003002815,0.0007539111,0.001071749,0.01392947,0.0008058154],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003869563,0.000005320475,0.00003786878,0.0002356333,0.00001687961,0.00007202183,0.00001406873,0.0002460755,0.0002642658,0.0009146248,0.9924619,0.005692769],"study_design_scores_gemma":[0.00007642209,0.00004295087,0.0008339714,0.0001923185,0.00003680361,0.0003805649,0.00005836468,0.002784482,0.001939493,0.002947212,0.9906378,0.00006963986],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0004710542,0.00291556,0.007845036,0.02651382,0.9515427,0.00005919885,0.003721074,0.002677108,0.004254608],"genre_scores_gemma":[0.05124767,0.02085052,0.05996193,0.05522566,0.247915,0.0007599891,0.01800054,0.0139252,0.5321134],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1314868,"threshold_uncertainty_score":0.4398673,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005088197423715737,"score_gpt":0.176676329838415,"score_spread":0.1715881324146992,"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."}}