{"id":"W3096689883","doi":"10.1039/d0ma00579g","title":"Electronic and protonic transport in bio-sourced materials: a new perspective on semiconductivity","year":2020,"lang":"en","type":"article","venue":"Materials Advances","topic":"Conducting polymers and applications","field":"Materials Science","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Bioelectronics; Electronics; Electronic materials; Semiconductor; Nanotechnology; Organic semiconductor; Perspective (graphical); Materials science; Engineering; Electrical engineering; Computer science; Biosensor; Optoelectronics","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":[0.0005126897,0.0005539727,0.0007533604,0.0008089947,0.0005290494,0.002233275,0.0008514281,0.001945898,0.003624312],"category_scores_gemma":[0.0005538598,0.0002275898,0.0002971525,0.0004549801,0.003022098,0.005996537,0.001217127,0.00176003,0.0006987532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006649646,"about_ca_system_score_gemma":0.0003669044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001397831,"about_ca_topic_score_gemma":0.0002382614,"domain_scores_codex":[0.9998088,0.00004267188,0.000009242843,0.00003705418,0.00007093391,0.00003119733],"domain_scores_gemma":[0.9996587,0.0002030078,0.00002199215,0.00003661636,0.00005013739,0.00002941859],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000862237,0.0001113508,0.0001647555,0.001513719,0.00002517155,0.0004910352,0.0002778898,0.001156744,0.06394657,0.8684555,0.005944314,0.05782676],"study_design_scores_gemma":[0.00003016607,0.0003996178,0.000449551,0.0003868747,0.00003972485,0.001371835,0.0004883971,0.00594705,0.03680625,0.7267422,0.2272738,0.00006446669],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.06209658,0.6112168,0.07859842,0.04085056,0.004669346,0.00003742287,0.0002355786,0.000331391,0.2019638],"genre_scores_gemma":[0.4985217,0.4273696,0.02245903,0.006397665,0.008113884,0.0001056638,0.0001965293,0.0001780746,0.03665791],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003624312,"threshold_uncertainty_score":0.01212454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01924230454803004,"score_gpt":0.2798698578463545,"score_spread":0.2606275532983245,"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."}}