{"id":"W3045686195","doi":"10.1007/978-3-030-00928-1_100","title":"Correction to: Medical Image Computing and Computer Assisted Intervention – MICCAI 2018","year":2020,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Medical Imaging and Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Section (typography); Special section; Information retrieval; Data science; Library science; Operating system; Engineering physics; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005393624,0.0003389826,0.0004725235,0.0004177376,0.000107336,0.0002455453,0.0005092406,0.0001941818,0.00009187153],"category_scores_gemma":[0.000239879,0.0003203475,0.0001203019,0.0003587598,0.0003510664,0.0001240259,0.000413213,0.0009254285,0.00005136138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001519455,"about_ca_system_score_gemma":0.00006775137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003038921,"about_ca_topic_score_gemma":0.00004024004,"domain_scores_codex":[0.9977357,0.00002767323,0.0004648396,0.0007124743,0.0007241531,0.000335142],"domain_scores_gemma":[0.9988101,0.0002994098,0.00007798412,0.0002699495,0.00007948996,0.0004630628],"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":[0.000001770245,0.00001110954,0.00005368345,0.0001044437,0.00003046772,0.00007399816,0.0002462191,0.01240241,0.0001539625,0.00003036952,0.002059039,0.9848325],"study_design_scores_gemma":[0.000180642,0.00005547998,0.0002453842,0.001288125,0.00002234878,0.00007444596,3.043369e-7,0.9959363,0.0001967202,0.0005026856,0.001167254,0.0003303354],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0003487783,0.0002351267,0.9928008,0.0007931138,0.004440712,0.0001211456,0.000002816446,0.0002638395,0.0009937171],"genre_scores_gemma":[0.6898654,0.00009884728,0.2996593,0.005626221,0.004152865,0.000005785677,0.00006247951,0.0001482494,0.0003808621],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9845022,"threshold_uncertainty_score":0.9999248,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01006747564796312,"score_gpt":0.2495182925263927,"score_spread":0.2394508168784296,"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."}}