{"id":"W2941507793","doi":"10.1002/adma.201808256","title":"Toward Design of Novel Materials for Organic Electronics","year":2019,"lang":"en","type":"review","venue":"Advanced Materials","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":167,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Agence Nationale de la Recherche; European Commission; Baden-Württemberg Stiftung","keywords":"Materials science; Nanotechnology; Organic electronics; Electronics; Organic solar cell; Transistor; Photovoltaics; Identification (biology); Thin-film transistor; Computer science; Biochemical engineering; Photovoltaic system; Electrical engineering; Polymer; Engineering","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":[0.0006068644,0.0007354915,0.0007035559,0.001832901,0.0003254808,0.001108009,0.0008480884,0.001338666,0.003441262],"category_scores_gemma":[0.0005405428,0.0004100949,0.0004786393,0.001241673,0.0005698897,0.001977598,0.0009527131,0.002118532,0.002516633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006746317,"about_ca_system_score_gemma":0.000851244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004171841,"about_ca_topic_score_gemma":0.0008742419,"domain_scores_codex":[0.9998203,0.00003159556,0.00001783946,0.00003440063,0.00007229661,0.00002346004],"domain_scores_gemma":[0.9998481,0.0000709089,0.00001995291,0.00001061536,0.00004039866,0.0000100606],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003236462,0.0001353179,0.0001502293,0.01835636,0.00008572065,0.0003188711,0.0001323142,0.002381544,0.02606777,0.1520477,0.02380531,0.7764864],"study_design_scores_gemma":[0.000007207156,0.00004540162,0.000131493,0.001636309,0.0000295567,0.0004633264,0.00003627113,0.0006890378,0.004852795,0.0148612,0.977231,0.00001643399],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0006223516,0.9867538,0.004952559,0.0007130631,0.0004738866,0.00002424126,0.00004239573,0.0000350839,0.006382643],"genre_scores_gemma":[0.004621655,0.9853071,0.00640445,0.0003542925,0.0002426592,0.00004516703,0.0000676726,0.00001122651,0.002945779],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003441262,"threshold_uncertainty_score":0.01151222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08101315956370493,"score_gpt":0.3573631223551741,"score_spread":0.2763499627914692,"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."}}