{"id":"W2621167442","doi":"10.1016/j.jtherbio.2017.05.008","title":"Fast inverse prediction of the freezing front in cryosurgery","year":2017,"lang":"en","type":"review","venue":"Journal of Thermal Biology","topic":"Thermoelastic and Magnetoelastic Phenomena","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cryosurgery; Bioheat transfer; Thermocouple; Materials science; Heat transfer; Biomedical engineering; Ablation; Mechanics; Inverse; Ultrasound; Inverse problem; Liquid nitrogen; Nuclear magnetic resonance; Thermodynamics; Chemistry; Composite material; Physics; Acoustics; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005698104,0.0008838119,0.001129703,0.0005692163,0.0001099154,0.0008070628,0.0009841622,0.001048587,0.00145967],"category_scores_gemma":[0.001146405,0.0005181496,0.0006340351,0.0004716516,0.0004931237,0.0008429736,0.0006440713,0.001087972,0.0006722791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002546485,"about_ca_system_score_gemma":0.0004609775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009960429,"about_ca_topic_score_gemma":0.0009599,"domain_scores_codex":[0.9998721,0.00002145549,0.000008176222,0.0000264928,0.00006274469,0.000008981066],"domain_scores_gemma":[0.9996177,0.000221427,0.00004362498,0.00001718918,0.00008948183,0.0000105474],"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":[0.0001637786,0.0001107719,0.0009462342,0.007548024,0.0001716765,0.0002514746,0.00009820193,0.1224484,0.02888359,0.01486994,0.006041328,0.8184667],"study_design_scores_gemma":[0.00008273297,0.0003209567,0.003009358,0.001966878,0.0003702725,0.001611714,0.0001031246,0.8058836,0.06053143,0.02757356,0.0983236,0.0002228679],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0136687,0.6541219,0.3240745,0.0008033487,0.001057998,0.00005295845,0.000157388,0.0005314436,0.005531752],"genre_scores_gemma":[0.1940252,0.7021771,0.09467636,0.0003537952,0.001428945,0.0001077119,0.0003598036,0.0001857542,0.006685294],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.00145967,"threshold_uncertainty_score":0.004883051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04472883764177935,"score_gpt":0.2632084152434191,"score_spread":0.2184795776016398,"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."}}