{"id":"W3214651164","doi":"10.32920/ryerson.14653362.v1","title":"A Context Based Automated System for Lung Nodule Detection in CT Images","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Lung Cancer Diagnosis and Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"","keywords":"Context (archaeology); Computer science; Nodule (geology); Lung; Artificial intelligence; Segmentation; Computer vision; Minimum bounding box; Pattern recognition (psychology); Image (mathematics); Medicine; Biology","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":[0.0004756457,0.0006963999,0.0007745144,0.001252155,0.0004470684,0.0006905813,0.0009158346,0.001090339,0.005338646],"category_scores_gemma":[0.001359703,0.0003999445,0.0004618858,0.0005543026,0.0001705612,0.0005730701,0.000822596,0.00051258,0.002487964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002168842,"about_ca_system_score_gemma":0.0005454932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001486729,"about_ca_topic_score_gemma":0.00239315,"domain_scores_codex":[0.9994932,0.00008447438,0.00003124733,0.0001855004,0.0001604428,0.00004508545],"domain_scores_gemma":[0.9996153,0.0001162218,0.00003494986,0.00009019872,0.0001029531,0.00004031191],"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":[0.0006414497,0.0001388117,0.003477718,0.0003599831,0.0001109659,0.0004643899,0.0001396316,0.006231951,0.2699236,0.001340014,0.008576872,0.7085946],"study_design_scores_gemma":[0.0002381443,0.0009166997,0.02896938,0.0001469305,0.0003287918,0.004648642,0.0001634569,0.6134623,0.2887765,0.0043057,0.05784484,0.0001986295],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0828683,0.001897869,0.8587371,0.0002084949,0.0001562945,0.0004909993,0.001424867,0.05133673,0.00287939],"genre_scores_gemma":[0.2496002,0.0006259344,0.743679,0.0002035515,0.0001575442,0.0003202059,0.001750506,0.0006764209,0.002986825],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005338646,"threshold_uncertainty_score":0.01785952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01436514630038394,"score_gpt":0.3013983226832077,"score_spread":0.2870331763828237,"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."}}