{"id":"W2159604677","doi":"10.1109/tmi.2003.819919","title":"An Analytic Method to Predict the Thermal Map of Cryosurgery Iceballs in MR Images","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Imaging","topic":"Infrared Thermography in Medicine","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; IMRIS (Canada); Centre hospitalier universitaire de Québec","funders":"","keywords":"Volume (thermodynamics); Cryosurgery; Magnetic resonance imaging; Materials science; SIGNAL (programming language); Nuclear magnetic resonance; Thermal; Sensitivity (control systems); Range (aeronautics); Temperature measurement; Phase (matter); Optics; Physics; Computer science; Radiology; Thermodynamics","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":[0.0004540836,0.0007233639,0.0004380404,0.0008649231,0.0002287554,0.0004233041,0.0007466769,0.0005545317,0.001050189],"category_scores_gemma":[0.002740774,0.0004199755,0.0004451456,0.0003218944,0.0005040455,0.0006280641,0.0003149291,0.0007469908,0.0006491294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003843738,"about_ca_system_score_gemma":0.000480248,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001032498,"about_ca_topic_score_gemma":0.001072962,"domain_scores_codex":[0.9998429,0.00002790109,0.000006262876,0.00004265689,0.00006975641,0.00001052684],"domain_scores_gemma":[0.9994836,0.0002544971,0.00008126719,0.00004628751,0.0001187722,0.00001559189],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002237563,0.00007758872,0.002582904,0.0003119207,0.0001021542,0.0002431859,0.0002320455,0.444411,0.2716965,0.009294573,0.001920193,0.2689042],"study_design_scores_gemma":[0.000008608459,0.00004795999,0.0009700339,0.00001456089,0.00002584695,0.0001481507,0.00001999459,0.9619305,0.03264353,0.002195874,0.001970164,0.00002475514],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0079151,0.0001084525,0.9911509,0.00003382421,0.00001643649,0.00001553391,0.00003628368,0.0004796515,0.0002439597],"genre_scores_gemma":[0.2619838,0.0005725113,0.735351,0.00005015484,0.00007261657,0.0001777677,0.0001526641,0.000294966,0.001344494],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001050189,"threshold_uncertainty_score":0.003513277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01056636721466074,"score_gpt":0.3143866765436378,"score_spread":0.303820309328977,"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."}}