{"id":"W2591588689","doi":"10.1109/memc.2016.7866253","title":"IEEE Women in Engineering","year":2016,"lang":"en","type":"article","venue":"IEEE Electromagnetic Compatibility Magazine","topic":"Gender Diversity and Inequality","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Telecommunications; Engineering; Library science; Event (particle physics); Political science; Computer science; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003210716,0.000917831,0.0004854045,0.001545068,0.00457399,0.006923032,0.001064646,0.003037672,0.1348664],"category_scores_gemma":[0.005909803,0.0003094064,0.0003893664,0.001414108,0.002632692,0.003929096,0.004719151,0.003744789,0.05152644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003511707,"about_ca_system_score_gemma":0.006120268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005050964,"about_ca_topic_score_gemma":0.01077916,"domain_scores_codex":[0.9967324,0.0008136693,0.0001651423,0.0003965065,0.001386795,0.0005056072],"domain_scores_gemma":[0.9971994,0.0003726023,0.0001139589,0.0002619499,0.001139584,0.000912545],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001956627,0.00002731708,0.0005715641,0.0001857271,0.000003821536,0.00008395601,0.001674048,0.00003995796,0.0002872491,0.0542684,0.7830235,0.1598149],"study_design_scores_gemma":[6.731179e-7,0.000005708334,0.0002113454,0.00008888538,8.367458e-7,0.00006984449,0.0003840978,0.000007814804,0.00003580843,0.001775489,0.9974173,0.000002251836],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001852524,0.05951169,0.002932372,0.09241893,0.02927889,0.00009943683,0.0003150206,0.0002910998,0.8133001],"genre_scores_gemma":[0.02450844,0.02602183,0.001575059,0.01361097,0.00425991,0.00008845429,0.0002200417,0.0001689854,0.9295463],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1348664,"threshold_uncertainty_score":0.4511729,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03472396656187326,"score_gpt":0.2582904618065886,"score_spread":0.2235664952447153,"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."}}