{"id":"W1739793028","doi":"","title":"Microwave breast tumor detection exploiting wideband Jacobians","year":2008,"lang":"en","type":"article","venue":"International Conference on Microwaves, Radar & Wireless Communications","topic":"Microwave Imaging and Scattering Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Jacobian matrix and determinant; Wideband; Solver; Computation; Computer science; Overhead (engineering); Finite-difference time-domain method; Algorithm; Convergence (economics); Electronic engineering; Mathematics; Applied mathematics; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001851146,0.0003606104,0.0003306127,0.0003800863,0.0005203995,0.000171211,0.00141619,0.000091605,0.0001814891],"category_scores_gemma":[0.00002655775,0.0004119214,0.0001965289,0.0003061463,0.0003234208,0.0002884019,0.0001932793,0.0006417285,0.0002587794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002848136,"about_ca_system_score_gemma":0.00007542051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000249151,"about_ca_topic_score_gemma":0.0004001808,"domain_scores_codex":[0.9982153,0.0001171217,0.0005802178,0.0003840202,0.0003180675,0.0003852297],"domain_scores_gemma":[0.9980438,0.0001244014,0.0001513936,0.001251393,0.0002874895,0.0001415581],"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":[0.00001996144,0.0001245851,0.0004884526,0.00001989854,0.0002371184,0.00002364041,0.0007976425,0.0003106521,0.9699566,0.001471774,0.001683967,0.02486568],"study_design_scores_gemma":[0.002465925,0.0001186492,0.005453196,0.001047031,0.0002091094,0.004601032,0.002635403,0.2509582,0.6824624,0.001487512,0.04566422,0.00289727],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8693611,0.0005769703,0.0717027,0.00361109,0.0008881819,0.0003518986,0.0003479399,0.001174964,0.05198518],"genre_scores_gemma":[0.9935009,0.001061912,0.004176039,0.0002634879,0.0001288518,0.00003246352,0.0002119029,0.00007621407,0.0005482155],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2874942,"threshold_uncertainty_score":0.9998333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03708671694363534,"score_gpt":0.2516875128049051,"score_spread":0.2146007958612698,"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."}}