{"id":"W2066274295","doi":"10.1002/jnm.512","title":"Use of lossless transmission‐line segments and shunt resistors for TLM diffusion modelling","year":2003,"lang":"en","type":"article","venue":"International Journal of Numerical Modelling Electronic Networks Devices and Fields","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Energy","funders":"","keywords":"Resistor; Lossless compression; Transmission line; Shunt (medical); Computer science; Electric power transmission; Electronic engineering; Electrical engineering; Voltage; Engineering; Algorithm; Telecommunications; Data compression","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000251787,0.0001407638,0.0002772551,0.00009536368,0.00004249058,0.00003876895,0.0001106222,0.0001219289,0.0000143807],"category_scores_gemma":[0.00001711229,0.0001205013,0.00009618547,0.00009131401,0.00002623425,0.0001376247,0.000009658488,0.0003033788,4.178377e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004333934,"about_ca_system_score_gemma":0.00002209302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001044463,"about_ca_topic_score_gemma":0.00000119625,"domain_scores_codex":[0.9988794,0.00004722373,0.0005018172,0.0001288453,0.0002129033,0.00022986],"domain_scores_gemma":[0.9990949,0.0004263495,0.0001510653,0.00005853014,0.0001637918,0.0001053813],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001194984,0.00003739683,0.0001484475,0.00002103378,0.0001009971,0.000001312544,0.00007016182,0.9778407,0.00005994474,0.001123603,0.00002161595,0.02045534],"study_design_scores_gemma":[0.0005025197,0.0003145391,0.00002273794,0.00008936908,0.00004607864,0.00002327587,0.000008156972,0.9902242,0.00009703397,0.003530215,0.005021004,0.0001208523],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05248873,0.004623923,0.9424227,0.0001371222,0.0002046863,0.00007980769,0.000001253464,0.00001226176,0.00002953952],"genre_scores_gemma":[0.9449317,0.004514104,0.05030739,0.00009606422,0.00009984298,0.0000024179,0.000002199178,0.00001905693,0.00002721462],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.892443,"threshold_uncertainty_score":0.49139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02915506046376011,"score_gpt":0.2685189322460609,"score_spread":0.2393638717823008,"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."}}