{"id":"W2545251632","doi":"10.1109/ias.1998.729808","title":"Calorimetric calibration of spark gaps for electrostatic discharge studies","year":2002,"lang":"en","type":"article","venue":"","topic":"Electrostatic Discharge in Electronics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Spark gap; Spark plug; SPARK (programming language); Electric spark; Electrostatic discharge; Calibration; Electromagnetic pulse; Energy (signal processing); Materials science; Electric potential energy; Spark chamber; Electrical engineering; Nuclear engineering; Optoelectronics; Optics; Physics; Voltage; Mechanical engineering; Engineering; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001724055,0.0009629522,0.001019137,0.001333348,0.0008609622,0.0006162585,0.001687923,0.001097049,0.003313585],"category_scores_gemma":[0.005227153,0.0004830488,0.0004422079,0.001708554,0.0005574198,0.0006721732,0.00116269,0.001491658,0.001190991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006263577,"about_ca_system_score_gemma":0.0008684612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006002388,"about_ca_topic_score_gemma":0.001292134,"domain_scores_codex":[0.99669,0.0004427564,0.0001708879,0.0004464965,0.002070961,0.0001789095],"domain_scores_gemma":[0.9971696,0.000854945,0.0002976081,0.000557386,0.001037805,0.00008272385],"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":[0.0001871571,0.0001399052,0.002117649,0.0004119686,0.00002900336,0.0001237455,0.0003030087,0.001358497,0.9685315,0.001920545,0.0008505099,0.02402659],"study_design_scores_gemma":[0.00001054606,0.0002119181,0.003041116,0.0000227287,0.00001748365,0.0002140378,0.0001135521,0.004440256,0.9849972,0.0003197611,0.006587436,0.00002409602],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4414362,0.003625013,0.5350871,0.0003029411,0.001002166,0.001377542,0.001842275,0.003120529,0.01220613],"genre_scores_gemma":[0.7699454,0.002731597,0.2126294,0.0002760561,0.0001025316,0.00210484,0.00223323,0.0006103173,0.009366757],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003313585,"threshold_uncertainty_score":0.01108497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02729717367591911,"score_gpt":0.2592216924979111,"score_spread":0.231924518821992,"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."}}