{"id":"W6901701814","doi":"10.60692/bwt7p-6jk30","title":"The Medical Segmentation Decathlon","year":2022,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Polytechnique Montréal","funders":"","keywords":"Segmentation; Task (project management); Set (abstract data type); Image segmentation; Image (mathematics); Scale-space segmentation; Segmentation-based object categorization; Range (aeronautics)","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":[0.01343116,0.002067493,0.001801076,0.002758695,0.002351275,0.004383055,0.003874675,0.004606733,0.007051989],"category_scores_gemma":[0.0311749,0.001092326,0.002418934,0.001721212,0.003470163,0.004417281,0.009879366,0.005615911,0.004357961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00315671,"about_ca_system_score_gemma":0.003404812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00262014,"about_ca_topic_score_gemma":0.004242353,"domain_scores_codex":[0.9875694,0.003654383,0.0007472275,0.003991468,0.003381764,0.0006558624],"domain_scores_gemma":[0.96987,0.01122729,0.00168695,0.00764806,0.00668424,0.002883552],"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":[0.003275198,0.001642191,0.01848632,0.003144657,0.000842138,0.0009578767,0.002213089,0.05035909,0.02921989,0.04226968,0.2712655,0.5763244],"study_design_scores_gemma":[0.0006794975,0.005858456,0.04275072,0.001152015,0.0002476657,0.004824299,0.002507001,0.2912014,0.08717652,0.1066062,0.4563659,0.0006302947],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.377462,0.02110334,0.4464493,0.03324629,0.01273353,0.005042959,0.02917387,0.008159931,0.06662871],"genre_scores_gemma":[0.4913156,0.002919844,0.4154582,0.00702226,0.002562404,0.003510127,0.03985232,0.002677237,0.03468207],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01343116,"threshold_uncertainty_score":0.07103163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02373047442053694,"score_gpt":0.2337900830950976,"score_spread":0.2100596086745607,"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."}}