{"id":"W2056310338","doi":"10.1088/0953-8984/23/5/055802","title":"Generalized lucky-drift model for impact ionization in semiconductors with disorder","year":2011,"lang":"en","type":"article","venue":"Journal of Physics Condensed Matter","topic":"Phase-change materials and chalcogenides","field":"Materials Science","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thunder Bay Regional Research Institute","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Impact ionization; Semiconductor; Ionization; Condensed matter physics; Statistical physics; Monte Carlo method; Amorphous semiconductors; Generalization; Physics; Materials science; Computational physics; Quantum mechanics; Mathematics; Statistics; Mathematical analysis","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":[0.0007646329,0.001042146,0.001397383,0.001021135,0.0009208347,0.001285172,0.002471941,0.002504837,0.004106976],"category_scores_gemma":[0.00111265,0.0004068251,0.001104198,0.0008636412,0.002126467,0.002189098,0.0009860237,0.001287752,0.0008404159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001653351,"about_ca_system_score_gemma":0.001385888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004923333,"about_ca_topic_score_gemma":0.003197178,"domain_scores_codex":[0.9997728,0.00005626339,0.000009462674,0.00002850569,0.00007280857,0.00006012631],"domain_scores_gemma":[0.9996827,0.00009846457,0.00004011313,0.00004155446,0.00008382265,0.00005342899],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006881219,0.00004696237,0.0003326828,0.00009993818,0.00002845667,0.0003639075,0.0001089508,0.3642068,0.004111359,0.6267539,0.001624759,0.002253492],"study_design_scores_gemma":[0.00001767525,0.00001881698,0.00008149066,0.000006328165,0.000005552812,0.00006006178,0.00001326412,0.9380503,0.0001739885,0.06084139,0.0007139263,0.0000172595],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1561229,0.005376533,0.7641508,0.003576086,0.000687935,0.0002738207,0.000874756,0.0006804847,0.06825675],"genre_scores_gemma":[0.8869973,0.002864664,0.03644243,0.0009140153,0.0003353237,0.0005636546,0.0004337566,0.0002258805,0.07122306],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004923333,"threshold_uncertainty_score":0.01373917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04769483553972872,"score_gpt":0.2744049611962274,"score_spread":0.2267101256564987,"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."}}