{"id":"W4229829969","doi":"10.1002/ima.20249","title":"Estimation of a dense velocity field based on the statistics of dynamic speckle","year":2010,"lang":"en","type":"article","venue":"International Journal of Imaging Systems and Technology","topic":"Ultrasound Imaging and Elastography","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Nautical Research Society","funders":"","keywords":"Autocovariance; Speckle pattern; Estimator; Standard deviation; Mathematics; Statistics; Magnitude (astronomy); Vector field; Range (aeronautics); Algorithm; Physics; Optics; Mathematical analysis; Geometry; Engineering","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":[0.000267098,0.00005610373,0.0001665999,0.0004095852,0.00001891949,0.00001188158,0.0001187802,0.00003961833,0.00001091388],"category_scores_gemma":[0.0006391517,0.00003733531,0.00003952513,0.0001025358,0.0001571034,0.00003138876,0.00001224597,0.0002770845,4.459018e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001275983,"about_ca_system_score_gemma":0.00005605744,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000453553,"about_ca_topic_score_gemma":0.000003851313,"domain_scores_codex":[0.999324,0.00001341722,0.0003278986,0.00005559939,0.0002208551,0.00005817953],"domain_scores_gemma":[0.9987763,0.0002475643,0.0003722631,0.0001041594,0.0004797962,0.00001998653],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007291717,0.0008026109,0.3637956,0.0003748436,0.0008204366,0.0001442009,0.0004660587,0.0005383275,0.32265,0.04934018,0.002934889,0.2574036],"study_design_scores_gemma":[0.007270612,0.00244705,0.08953546,0.004888525,0.000521394,0.01093088,0.002177543,0.8029574,0.0522262,0.01960598,0.00697918,0.0004598294],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9122003,0.0001520956,0.07975943,0.007000186,0.0006347814,0.00006562623,0.00001759034,0.000009986941,0.0001600179],"genre_scores_gemma":[0.9892683,0.00001496715,0.01058356,0.00008054685,0.00003224673,0.000001021853,0.000001503858,0.000004851543,0.00001300515],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.802419,"threshold_uncertainty_score":0.152249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003839786442729069,"score_gpt":0.2574585306993732,"score_spread":0.2536187442566442,"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."}}