{"id":"W3213451231","doi":"10.1007/s10825-021-01817-1","title":"Nanoelectronic circuit elements based on nanoscale metal–molecular networks","year":2021,"lang":"en","type":"article","venue":"Journal of Computational Electronics","topic":"Molecular Junctions and Nanostructures","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"Compute Canada","keywords":"Materials science; Delocalized electron; Rectification; Chemical physics; Electronic circuit; Topology (electrical circuits); Nanotechnology; Fermi level; Conductance; Nanoelectronics; Fermi energy; Density functional theory; Nanoscopic scale; Molecular electronics; Molecular physics; Molecule; Voltage; Electron; Condensed matter physics; Physics; Computational chemistry; Chemistry; Quantum mechanics; Electrical engineering","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":[0.00005482289,0.0001343107,0.0002357929,0.0002056324,0.0003322421,0.0006128568,0.0006440427,0.0004011586,0.004934406],"category_scores_gemma":[0.0003072101,0.0001378931,0.0001182947,0.0001476235,0.0003231085,0.0007832645,0.0003811405,0.0002894016,0.0006728163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003038232,"about_ca_system_score_gemma":0.0001228208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002459304,"about_ca_topic_score_gemma":0.0007242523,"domain_scores_codex":[0.9999493,0.00001080448,0.000002291691,0.00001058406,0.00001754037,0.000009515732],"domain_scores_gemma":[0.9999392,0.00002353887,0.000007962859,0.00001282065,0.000009733937,0.000006669544],"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":[0.0001936211,0.0001755846,0.0005671337,0.000260463,0.00005324206,0.0002690219,0.0002002474,0.06669274,0.2462785,0.6457003,0.004367046,0.03524211],"study_design_scores_gemma":[0.00006992997,0.0003230952,0.001219146,0.0000651819,0.00006323186,0.0002542782,0.0001149533,0.6312354,0.1485715,0.1393449,0.07868361,0.0000547543],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6495706,0.001353992,0.1861823,0.001353371,0.0007265884,0.0001834898,0.0002336464,0.001050858,0.159345],"genre_scores_gemma":[0.9615455,0.0002315757,0.02536414,0.00009096681,0.00004073358,0.00006342796,0.00005458849,0.00004734253,0.01256174],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004934406,"threshold_uncertainty_score":0.01650721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004170704926969944,"score_gpt":0.2016219908286634,"score_spread":0.1974512859016935,"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."}}