{"id":"W3141858421","doi":"10.1109/imbioc47321.2020.9385029","title":"Comparative Study of Tissue-Mimicking Phantoms for Microwave Breast Cancer Screening Systems","year":2020,"lang":"en","type":"article","venue":"","topic":"Microwave Imaging and Scattering Analysis","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Imaging phantom; Microwave; Materials science; Biomedical engineering; Dielectric; Breast tissue; Human breast; Breast cancer; Microwave imaging; Cancer; Optoelectronics; Medicine; Radiology; Computer science; Internal medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008433291,0.0001684015,0.0004482517,0.00007040316,0.00005206896,0.0000513585,0.0001504718,0.00002770975,0.00002840282],"category_scores_gemma":[0.000003132689,0.0001574461,0.00006339091,0.0002258689,0.00001800425,0.00007261818,0.00002705744,0.00008544708,0.000005399989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002540262,"about_ca_system_score_gemma":0.000006587444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005342893,"about_ca_topic_score_gemma":0.00006770643,"domain_scores_codex":[0.999121,0.00002495984,0.0003167453,0.0002120218,0.0001160698,0.0002092231],"domain_scores_gemma":[0.9995993,0.00004438009,0.00005861061,0.0001355145,0.00008186944,0.00008036158],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004020026,0.00007280806,0.003959233,0.000454117,0.001094146,0.000004129951,0.01380901,0.3344587,0.6357942,0.00001202046,0.005297666,0.005003767],"study_design_scores_gemma":[0.001153527,0.0001147215,0.001027548,0.0001331653,0.0002664576,0.00001212364,0.0133202,0.8923708,0.09035226,0.000001388042,0.0008403742,0.0004073985],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7272352,0.0005884054,0.270598,0.0001765231,0.0001404759,0.0004614179,0.0000774119,0.0002640507,0.0004585805],"genre_scores_gemma":[0.998571,0.000007651199,0.001104742,0.0000343068,0.0001305576,0.00004308503,0.000007236773,0.00002905413,0.00007241627],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5579122,"threshold_uncertainty_score":0.6420465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04378013999414506,"score_gpt":0.2902476046795496,"score_spread":0.2464674646854046,"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."}}