{"id":"W1974361535","doi":"10.1109/ultsym.2014.0110","title":"High-resolution blood flow imaging through the skull","year":2014,"lang":"en","type":"article","venue":"","topic":"Microwave Imaging and Scattering Analysis","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Office of Naval Research","keywords":"Skull; Ultrasound; Blood flow; Computer science; Scanner; Ultrasonic sensor; Radiology; Battlefield; Magnetic resonance imaging; Ultrasonic imaging; Biomedical engineering; Medicine; Computer vision; Artificial intelligence; Anatomy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003339317,0.0003978949,0.0002460287,0.0006175973,0.000119534,0.0004426907,0.0002650314,0.0005085856,0.001465098],"category_scores_gemma":[0.0006362603,0.0002815215,0.0002567414,0.0002712384,0.0002954792,0.0006180109,0.0002910508,0.0002532271,0.0002122987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000167662,"about_ca_system_score_gemma":0.000221791,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00103672,"about_ca_topic_score_gemma":0.0007993524,"domain_scores_codex":[0.9999499,0.00001140006,0.000003331157,0.000008294899,0.00002018659,0.000006927516],"domain_scores_gemma":[0.9997845,0.0001182595,0.00003127895,0.00002057454,0.00003086237,0.00001459133],"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":[0.0002799165,0.00008560548,0.001209457,0.0001992433,0.00003416106,0.0006359406,0.0001763442,0.05187379,0.9006579,0.001917827,0.000358964,0.04257085],"study_design_scores_gemma":[0.0001098323,0.0004597344,0.006759567,0.00004774211,0.00006947992,0.002574992,0.0002124625,0.4081396,0.5762743,0.001918952,0.003367156,0.00006629201],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4983694,0.001006728,0.4948825,0.0002082103,0.00003722397,0.00007345044,0.000177629,0.0009575793,0.00428729],"genre_scores_gemma":[0.8230557,0.0009083219,0.1741411,0.00004592218,0.00001878196,0.00002466138,0.0001097698,0.00004955494,0.001646302],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001465098,"threshold_uncertainty_score":0.00490129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004446980764549873,"score_gpt":0.1814315815882048,"score_spread":0.1769846008236549,"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."}}