{"id":"W2803122122","doi":"10.3390/s18061678","title":"Evaluation of Image Reconstruction Algorithms for Confocal Microwave Imaging: Application to Patient Data","year":2018,"lang":"en","type":"article","venue":"Sensors","topic":"Microwave Imaging and Scattering Analysis","field":"Engineering","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Science Foundation Ireland; Alberta Innovates; Alberta Innovates - Health Solutions; Alberta Innovates - Technology Futures","keywords":"Algorithm; Microwave imaging; Computer science; Iterative reconstruction; Image quality; Artificial intelligence; Reconstruction algorithm; Image processing; Computer vision; Image (mathematics); Microwave","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004590113,0.0007002926,0.0005193516,0.001026683,0.0002732349,0.0007317917,0.0007391069,0.0008246063,0.001213176],"category_scores_gemma":[0.01734162,0.0002773183,0.0005453741,0.0009387764,0.000430933,0.0005070773,0.000558858,0.000501443,0.0002998578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005042922,"about_ca_system_score_gemma":0.0008760944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002130459,"about_ca_topic_score_gemma":0.002347771,"domain_scores_codex":[0.9984475,0.0006629457,0.000139274,0.0001581575,0.0005401865,0.00005192707],"domain_scores_gemma":[0.9911625,0.005923597,0.0004488194,0.0007794088,0.001595723,0.00008992865],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002835085,0.0007083496,0.03002314,0.0007483383,0.0003686692,0.0005497563,0.0008638559,0.2601092,0.1543036,0.002708581,0.001226545,0.5455549],"study_design_scores_gemma":[0.0001849418,0.001249333,0.01624423,0.00004298609,0.0001341717,0.002166726,0.0003201706,0.8039604,0.1720393,0.0008310255,0.002722332,0.0001044026],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4592411,0.0006046615,0.5365682,0.0002618851,0.000037042,0.0005417859,0.0003813267,0.00113068,0.001233244],"genre_scores_gemma":[0.4132006,0.000357533,0.5849987,0.00006399379,0.000009481786,0.000218185,0.0004673149,0.0002304867,0.0004538443],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004590113,"threshold_uncertainty_score":0.02427512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03317976394726615,"score_gpt":0.295453730584505,"score_spread":0.2622739666372389,"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."}}