{"id":"W4403494021","doi":"10.1561/116.20240044","title":"Automatic Medical Report Generation: Methods and Applications","year":2024,"lang":"en","type":"article","venue":"APSIPA Transactions on Signal and Information Processing","topic":"Advanced Text Analysis Techniques","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science","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":[0.0005528878,0.000108855,0.0001190575,0.0002795391,0.0003383449,0.0005507504,0.0001350132,0.00007517856,0.00006133478],"category_scores_gemma":[0.00001321813,0.00009214935,0.00003387265,0.0005782606,0.00006239593,0.004962514,0.00001006163,0.0001806111,0.0000124828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002600657,"about_ca_system_score_gemma":0.000115448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002823491,"about_ca_topic_score_gemma":7.715522e-7,"domain_scores_codex":[0.9989645,0.00003343169,0.0004055225,0.000198764,0.0002893609,0.000108351],"domain_scores_gemma":[0.9995036,0.00007880331,0.00007577745,0.0001547712,0.00008797723,0.00009908638],"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":[3.64715e-7,0.00000876007,8.206911e-7,0.00007480056,0.00001107359,0.000002570466,0.0003128112,0.0000725091,0.0001033678,0.01058684,0.0000326505,0.9887934],"study_design_scores_gemma":[0.00005777701,0.00002549598,0.00001784075,0.00007318206,0.00002223729,0.000346501,0.00004194935,0.9582738,0.003487589,0.004649524,0.03287429,0.0001297575],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001482919,0.0004630279,0.9963116,0.001146479,0.00003918515,0.0001409914,0.000001096333,0.000562395,0.001186937],"genre_scores_gemma":[0.4581769,0.000198724,0.5403391,0.0008300607,0.00006146556,0.0002538213,0.00001500342,0.000007422477,0.0001176364],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9886637,"threshold_uncertainty_score":0.5310898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01551352571246318,"score_gpt":0.3377518521077463,"score_spread":0.3222383263952831,"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."}}