{"id":"W4225395043","doi":"10.1109/radarconf2248738.2022.9764256","title":"[Front matter]","year":2022,"lang":"en","type":"article","venue":"2022 IEEE Radar Conference (RadarConf22)","topic":"Biomedical and Engineering Education","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lockheed Martin (Canada)","funders":"Air Force Research Laboratory; Air Force Institute of Technology; Università di Pisa; Army Research Laboratory; University of Electronic Science and Technology of China; Nederlandse Organisatie voor Toegepast Natuurwetenschappelijk Onderzoek; Politechnika Warszawska; University of Toronto; Università degli Studi di Napoli Federico II; University of Oklahoma; Arizona State University; IEEE Foundation; Aalto-Yliopisto; Research Institute, Georgia Institute of Technology","keywords":"Front (military); Creativity; Systems engineering; Engineering; Radar; Engineering management; Computer science; Phased array; Telecommunications; Political science; Mechanical engineering","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0005534875,0.001150985,0.0009711129,0.001381492,0.002262593,0.006949618,0.001056355,0.003017737,0.9226843],"category_scores_gemma":[0.0039805,0.0005431331,0.0008207964,0.001273173,0.0005335946,0.001922398,0.001117509,0.002177309,0.9278129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007663227,"about_ca_system_score_gemma":0.001679555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002738976,"about_ca_topic_score_gemma":0.004819218,"domain_scores_codex":[0.9993821,0.00002896642,0.00004170472,0.0001240649,0.0003235762,0.00009958912],"domain_scores_gemma":[0.9972349,0.0002325589,0.0001193474,0.0002617028,0.001536376,0.000615162],"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":[0.00002220934,0.00002731292,0.00008191404,0.00008499666,0.000003692396,0.00004785392,0.000007286083,0.00001531415,0.0003570304,0.0006100769,0.9543301,0.04441221],"study_design_scores_gemma":[0.000009371845,0.00001315004,0.0003007656,0.00004701594,0.000001965823,0.00006651337,0.00001327897,0.00002636322,0.0001614413,0.0002914739,0.9990633,0.000005493353],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000391975,0.0007478867,0.0006976291,0.003922772,0.01085548,0.0001792944,0.003554105,0.002550779,0.9771],"genre_scores_gemma":[0.00122391,0.0005316322,0.0003143538,0.002577575,0.001483458,0.00004200897,0.001889387,0.0005807378,0.991357],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.07731575,"threshold_uncertainty_score":0.1102815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01121144473774347,"score_gpt":0.1984968230855572,"score_spread":0.1872853783478138,"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."}}