{"id":"W3092490063","doi":"10.1016/j.media.2020.101861","title":"Sequential conditional reinforcement learning for simultaneous vertebral body detection and segmentation with modeling the spine anatomy","year":2020,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Medical Imaging and Analysis","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Segmentation; Artificial intelligence; Computer science; Minimum bounding box; Pattern recognition (psychology); Reinforcement learning; Context (archaeology); Deep learning; Feature (linguistics); Image segmentation; Artificial neural network; Computer vision; Image (mathematics)","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":[0.0002300188,0.0001367782,0.0002450263,0.0000994352,0.0001841587,0.00007618789,0.00009207348,0.00005240824,0.0003389944],"category_scores_gemma":[0.0003420819,0.00009419903,0.0001273033,0.0005436685,0.00008906169,0.0001219773,0.00002253081,0.000258504,0.000006190989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003243511,"about_ca_system_score_gemma":0.00001927329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004288603,"about_ca_topic_score_gemma":0.00002071646,"domain_scores_codex":[0.9987329,0.00003998637,0.000270149,0.0002118438,0.0005443549,0.0002007339],"domain_scores_gemma":[0.9994817,0.00007680378,0.00003982606,0.00007902332,0.00007882025,0.0002438153],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000009248257,0.000007292184,0.0001228151,0.00005072114,0.001252541,0.00002531621,0.0001985097,0.9854934,0.004429252,0.000009924056,0.00005999485,0.008340948],"study_design_scores_gemma":[0.0005536949,0.00004214655,0.00001479761,0.00001008272,0.001507664,0.000004559085,0.0002458122,0.9959792,0.001309282,0.00001673299,0.0001946376,0.0001214263],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.061982,0.00008306307,0.9362802,0.001362879,0.0000178963,0.0001004515,0.000002584878,0.000117034,0.00005389492],"genre_scores_gemma":[0.9977333,0.00005506457,0.001209046,0.0005129472,0.0001769906,0.00003236709,0.0002310395,0.00001592482,0.00003333318],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9357513,"threshold_uncertainty_score":0.3841325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007901384006566854,"score_gpt":0.2494513665996793,"score_spread":0.2415499825931125,"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."}}