{"id":"W4317794923","doi":"10.1109/mdat.2022.3221921","title":"Interview With Janet Olson","year":2023,"lang":"en","type":"article","venue":"IEEE Design and Test","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Tribute; Management; Semiconductor industry; Electronic design automation; Robotics; Automation; Engineering; Automotive industry; Manufacturing engineering; Engineering management; Sociology; Telecommunications; Computer science; Electrical engineering; Artificial intelligence; Art history; Robot; Art; Mechanical engineering","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":[0.00009335449,0.00006306002,0.00006305345,0.00004338849,0.00002405312,0.00002969515,0.00003500181,0.00002533303,0.00001957209],"category_scores_gemma":[0.00001329053,0.00005154658,0.000007937969,0.0001871175,0.00001172903,0.00003384355,0.000002983913,0.000048685,0.0001190066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004649956,"about_ca_system_score_gemma":0.000003961099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.645989e-7,"about_ca_topic_score_gemma":6.127552e-7,"domain_scores_codex":[0.9997211,0.000009584151,0.00005574172,0.00007087563,0.00004597009,0.00009677611],"domain_scores_gemma":[0.9997618,0.0001153151,0.000005964347,0.00006437552,0.0000114855,0.00004112621],"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":[0.00001119812,0.00004320767,0.001274638,0.0002465481,0.00008508644,0.0001283694,0.0009105292,0.85782,0.002050911,0.0001641168,0.03011898,0.1071464],"study_design_scores_gemma":[0.0002703475,0.00007163094,0.0007201033,0.00006632419,0.000010005,0.00001801674,0.00003971943,0.9940733,0.002173299,0.00003866946,0.002379664,0.0001389439],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0323283,0.0008401731,0.9607071,0.0004111172,0.0005861424,0.0002913634,0.00000943224,0.002422378,0.002403996],"genre_scores_gemma":[0.9208264,0.0007528945,0.07678133,0.0002678891,0.0001548589,0.00004019863,0.00001927806,0.00006691751,0.001090267],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8884981,"threshold_uncertainty_score":0.2102008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03046800255820365,"score_gpt":0.2209143426695793,"score_spread":0.1904463401113757,"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."}}