{"id":"W1972247226","doi":"10.1109/tmi.2012.2224667","title":"Transcranial Thermoacoustic Tomography: A Comparison of Two Imaging Algorithms","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Imaging","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Tomography; Aliasing; Computer science; Noise (video); Image quality; Transcranial Doppler; Neuroimaging; Acoustics; Computer vision; Artificial intelligence; Algorithm; Image (mathematics); Optics; Physics; Radiology; Medicine","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":[0.001517852,0.0007936988,0.0005785385,0.002184514,0.0002794077,0.001480686,0.0007824412,0.001140853,0.00143118],"category_scores_gemma":[0.006037307,0.0002624749,0.0004550877,0.001202151,0.0004237078,0.001891865,0.0007346701,0.0005856061,0.0004159521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003938732,"about_ca_system_score_gemma":0.0004996627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000984618,"about_ca_topic_score_gemma":0.0008544376,"domain_scores_codex":[0.999141,0.0002055507,0.0000675979,0.000133478,0.0003960137,0.00005624853],"domain_scores_gemma":[0.9972549,0.001291848,0.0002839251,0.0002630583,0.0007934693,0.0001128883],"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":[0.002670737,0.0002295224,0.009835536,0.0007523926,0.0003587675,0.0002165519,0.000277998,0.04507604,0.08743437,0.007436224,0.001813781,0.8438981],"study_design_scores_gemma":[0.0004250856,0.001579363,0.02718339,0.0002001818,0.0004720427,0.004357431,0.00054937,0.8248222,0.1209797,0.005017922,0.01407881,0.0003345292],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1422874,0.007873376,0.8424584,0.0004002518,0.0002878445,0.0001595412,0.0001647958,0.00173945,0.004628779],"genre_scores_gemma":[0.439326,0.003655981,0.5542285,0.00009727771,0.0000942447,0.0001215793,0.0003244781,0.0004789257,0.001673083],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002184514,"threshold_uncertainty_score":0.008027256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01113893388268705,"score_gpt":0.2752337140907454,"score_spread":0.2640947802080584,"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."}}