{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001383322,0.0001869225,0.0003110017,0.0001892662,0.00004892161,0.00001686045,0.0001246669,0.00005184882,0.0001228859],"category_scores_gemma":[0.0001807659,0.0001683869,0.00007986734,0.0005768692,0.00003451154,0.0001974139,0.00001075503,0.0001118375,0.0000137469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001106818,"about_ca_system_score_gemma":0.00001248028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000423677,"about_ca_topic_score_gemma":0.00002279895,"domain_scores_codex":[0.9987561,0.00001732617,0.0003849656,0.0001670087,0.0001831336,0.0004914847],"domain_scores_gemma":[0.9993037,0.0002991552,0.00005431614,0.0001979278,0.00009154959,0.00005335836],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007355545,0.0006158956,0.001346116,0.003457676,0.00217794,0.000003311422,0.005377084,0.01675441,0.3148755,0.2323814,0.4052169,0.01772025],"study_design_scores_gemma":[0.0009588464,0.0006174165,0.00003588563,0.0000397722,0.0001179761,0.000004090029,0.0001834385,0.5419697,0.4414575,0.009594457,0.004530881,0.0004900399],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4479641,0.05564842,0.477942,0.001019321,0.001241017,0.002973334,0.00014452,0.001543413,0.01152387],"genre_scores_gemma":[0.991906,0.001461618,0.005034974,0.00005565568,0.00007838548,0.0001230387,0.00002351675,0.00006048673,0.001256255],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.543942,"threshold_uncertainty_score":0.6866618,"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."}}