{"id":"W4402062094","doi":"10.1016/b978-0-443-15999-2.00009-8","title":"Deployment, feature extraction, and selection in computer vision and medical imaging","year":2024,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Software deployment; Computer vision; Computer science; Artificial intelligence; Feature selection; Feature extraction; Selection (genetic algorithm); Medical physics; Medicine; Software 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007747267,0.001168168,0.001137607,0.001599983,0.0004842096,0.002228853,0.001561677,0.001533931,0.009732905],"category_scores_gemma":[0.001401309,0.0009283322,0.0006611238,0.004284408,0.001276478,0.002769452,0.0009002052,0.001615017,0.007035877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006993372,"about_ca_system_score_gemma":0.0005259424,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00241548,"about_ca_topic_score_gemma":0.003104516,"domain_scores_codex":[0.9993145,0.0001225142,0.0000447706,0.0001856695,0.0002869087,0.00004562741],"domain_scores_gemma":[0.9992871,0.0004020415,0.0000332372,0.0001337583,0.0001207664,0.00002309902],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003993145,0.00003722351,0.0002193425,0.0003683581,0.00002022474,0.00007828286,0.00008728155,0.005473811,0.01150302,0.02110209,0.0267651,0.9343054],"study_design_scores_gemma":[0.00003000537,0.0002812824,0.004294765,0.0004255476,0.0001032652,0.00265443,0.0003359367,0.3588399,0.05362964,0.1938282,0.3854439,0.0001330879],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002244753,0.01663064,0.9677609,0.0007039082,0.0003217245,0.00006216409,0.0001387744,0.002280254,0.009856781],"genre_scores_gemma":[0.04315366,0.02627659,0.8797574,0.0004453476,0.0006633986,0.0001574947,0.000680829,0.001014761,0.04785057],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009732905,"threshold_uncertainty_score":0.03255981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0073459542732033,"score_gpt":0.2825848716421276,"score_spread":0.2752389173689244,"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."}}