{"id":"W1543519699","doi":"10.1002/0470094168.ch15","title":"The Roadmap for Recognizing Regions of Interest in Medical Images","year":2005,"lang":"en","type":"other","venue":"","topic":"AI in cancer detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lakehead University","funders":"","keywords":"Computer science; Artificial intelligence; Data science; Cartography; Geography","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":[0.0005310251,0.0007814085,0.0006730484,0.002632358,0.0004420345,0.001412689,0.001376323,0.001212361,0.01835185],"category_scores_gemma":[0.002866624,0.0003957869,0.0007458729,0.001504047,0.0004295128,0.001258777,0.001349807,0.0008128235,0.009558478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003361029,"about_ca_system_score_gemma":0.0008835782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004649832,"about_ca_topic_score_gemma":0.006152085,"domain_scores_codex":[0.999626,0.00006167973,0.00001547969,0.00008262804,0.000182861,0.00003127569],"domain_scores_gemma":[0.9993582,0.0001987586,0.00003253941,0.000137865,0.0002269812,0.00004563315],"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":[0.0001227228,0.00005114957,0.0006459967,0.0002956077,0.00005207222,0.0001330531,0.00004599356,0.007848602,0.008754029,0.009896827,0.06939756,0.9027563],"study_design_scores_gemma":[0.00008528567,0.0002131447,0.003802783,0.0002085562,0.0001201981,0.001903983,0.0001404456,0.7172993,0.04269912,0.06668086,0.1667618,0.00008460107],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008745401,0.004512282,0.937328,0.0009122386,0.000394802,0.0003125061,0.001981263,0.021075,0.02473845],"genre_scores_gemma":[0.1022004,0.003572316,0.8606611,0.0003134521,0.0001608933,0.0003340141,0.003423949,0.0009741713,0.02835976],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01835185,"threshold_uncertainty_score":0.06139308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06834866045234671,"score_gpt":0.315082539177281,"score_spread":0.2467338787249343,"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."}}