{"id":"W4411210064","doi":"10.26434/chemrxiv-2025-sk168","title":"Degradation-assisted doping of organic semiconductors: a strategy towards higher p-doping efficiency enabled by Lewis acids","year":2025,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"Organic Electronics and Photovoltaics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; York University; Institut National de la Recherche Scientifique","funders":"Fonds de recherche du Québec – Nature et technologies; Alliance de recherche numérique du Canada; Concordia University; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Doping; Degradation (telecommunications); Lewis acids and bases; Semiconductor; Organic semiconductor; Materials science; Nanotechnology; Chemistry; Optoelectronics; Organic chemistry; Computer science; Catalysis; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001347924,0.0002890049,0.0001555582,0.0001306916,0.0001350808,0.0003340992,0.0002244613,0.0003684519,0.0005890069],"category_scores_gemma":[0.0001408418,0.00008584325,0.0001353797,0.0001053135,0.0002585672,0.0003183751,0.0002722841,0.0003879034,0.0002537329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002181805,"about_ca_system_score_gemma":0.0001493355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003038783,"about_ca_topic_score_gemma":0.0003645435,"domain_scores_codex":[0.9998951,0.00001557595,0.000006358177,0.00002496742,0.0000299004,0.0000280621],"domain_scores_gemma":[0.9999392,0.00001593676,0.00001785571,0.000008857849,0.00000759383,0.00001045112],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000237978,0.00001181137,0.00008927311,0.00004739283,0.00000283463,0.00004387633,0.00001550624,0.0001674142,0.9967251,0.0005842971,0.00003550355,0.002253179],"study_design_scores_gemma":[0.000003205227,0.00005453142,0.0001165543,0.00000232144,0.000002084214,0.00006804321,0.00000634211,0.0008284713,0.9977451,0.00007786445,0.001092857,0.000002452359],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9698121,0.002463293,0.02332139,0.0002041229,0.00004247621,0.0000407085,0.0001133607,0.0001699781,0.003832613],"genre_scores_gemma":[0.9896597,0.0009519883,0.007764637,0.00005994088,0.000010692,0.00001703782,0.00006018725,0.00002513492,0.001450627],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005890069,"threshold_uncertainty_score":0.00197047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01692391966640513,"score_gpt":0.2347096333787599,"score_spread":0.2177857137123548,"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."}}