{"id":"W4295066874","doi":"10.7759/cureus.28980","title":"Use of Infrared Thermal Imaging for Assessing Acute Inflammatory Changes: A Case Series","year":2022,"lang":"en","type":"article","venue":"Cureus","topic":"Infrared Thermography in Medicine","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Medicine; Thermography; Inflammation; Erythema; Infrared; Radiology; Dermatology; Pathology; Internal medicine; Optics","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":[0.0007914761,0.003929824,0.001918871,0.004298192,0.004055455,0.002065655,0.001952156,0.007016598,0.002327516],"category_scores_gemma":[0.005171311,0.001685673,0.001839524,0.003094797,0.003405461,0.002867006,0.002821478,0.005871572,0.001318751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001704568,"about_ca_system_score_gemma":0.001037944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002347359,"about_ca_topic_score_gemma":0.003086125,"domain_scores_codex":[0.9981235,0.000248931,0.0003838284,0.0003612182,0.0003744624,0.0005081031],"domain_scores_gemma":[0.9975317,0.0006705862,0.0005364393,0.0002245553,0.0001972366,0.0008394319],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"case_report","study_design_gemma":"observational","study_design_scores_codex":[0.00001583359,0.00007271542,0.003884061,0.00004649723,0.00001458994,0.9928533,0.0003299394,0.0001153871,0.0004475744,0.0001616547,0.000350031,0.001708385],"study_design_scores_gemma":[0.000003854977,0.00002461609,0.001405508,0.00002502008,0.00001089052,0.9975151,0.0001643191,0.0001237531,0.0002111213,0.00009585499,0.0004077959,0.00001223708],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9069591,0.03328277,0.0266351,0.008671138,0.002151299,0.0007235435,0.0003566659,0.0004386202,0.02078176],"genre_scores_gemma":[0.9847625,0.005215202,0.004595603,0.001712714,0.001623674,0.0000909541,0.0001154417,0.00007406854,0.001809683],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007016598,"threshold_uncertainty_score":0.01236761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03424573765604227,"score_gpt":0.2990885270039923,"score_spread":0.26484278934795,"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."}}