{"id":"W2121881300","doi":"10.1109/iembs.2009.5333341","title":"A comparison of interpolation methods for breast microwave radar imaging","year":2009,"lang":"en","type":"article","venue":"","topic":"Microwave Imaging and Scattering Analysis","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; CancerCare Manitoba","funders":"","keywords":"Microwave imaging; Interpolation (computer graphics); Computer science; Radar imaging; Microwave; Image quality; Computer vision; Radar; Breast imaging; Artificial intelligence; Mammography; Iterative reconstruction; Image scaling; Breast cancer; Image processing; Image (mathematics); Medicine; Telecommunications","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":[0.0002140977,0.0001044114,0.0002390142,0.0001298325,0.00002581083,0.0000249279,0.00008952418,0.00002240151,0.00003084319],"category_scores_gemma":[0.00001079655,0.0001021866,0.0001152853,0.0001209316,0.00001499213,0.0000658128,0.000007267851,0.00006204392,0.000002962251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002386298,"about_ca_system_score_gemma":0.000003956189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001328063,"about_ca_topic_score_gemma":0.000002474326,"domain_scores_codex":[0.9993969,0.00002170967,0.000275538,0.000113626,0.00004108145,0.0001511141],"domain_scores_gemma":[0.9996768,0.00005311547,0.00003863872,0.0001562969,0.00004165892,0.00003354282],"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":[0.000004568627,0.00001343002,0.000664037,0.00002440218,0.00002757601,7.689913e-8,0.0002411406,0.0004447894,0.6781812,0.00008221113,0.001583085,0.3187335],"study_design_scores_gemma":[0.0001768702,0.000012836,0.001453056,0.00003136111,0.00005045462,0.00001278206,0.0001313087,0.7526404,0.2439913,0.0004446325,0.0009139974,0.0001409762],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01086439,0.0003858649,0.9855679,0.0002659929,0.00007651809,0.00006460839,0.000006458442,0.0001638011,0.002604507],"genre_scores_gemma":[0.687721,0.000002214644,0.3121544,0.00003674889,0.00002234759,0.000001372582,0.000007598557,0.000009419073,0.00004492495],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7521957,"threshold_uncertainty_score":0.4167047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01614523154400788,"score_gpt":0.343446381463956,"score_spread":0.3273011499199481,"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."}}