{"id":"W2545541238","doi":"","title":"Medical Image Computing and Computer-Assisted Intervention - Miccai 2003: 6th International Conference, Montreal, Canada, November 2003: Proceedings (LECTURE NOTES IN COMPUTER SCIENCE)","year":2004,"lang":"en","type":"article","venue":"Medical Image Computing and Computer-Assisted Intervention","topic":"AI in cancer detection","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer science; Multimedia; Library science; Data science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002519211,0.001327622,0.001476507,0.002063171,0.001125868,0.0032078,0.001806624,0.001308127,0.0302315],"category_scores_gemma":[0.002962705,0.0008437817,0.0006427241,0.002666386,0.001557408,0.001896536,0.001337328,0.001896316,0.008811737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002748586,"about_ca_system_score_gemma":0.006719631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1470524,"about_ca_topic_score_gemma":0.2475108,"domain_scores_codex":[0.9992834,0.0000845686,0.00003507064,0.0001072496,0.0003913882,0.00009834765],"domain_scores_gemma":[0.9975279,0.0002930421,0.00005044057,0.0001339665,0.001673845,0.0003208264],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002955741,0.000176426,0.001692994,0.0003702108,0.0001104009,0.00009476903,0.0001138565,0.002416818,0.005968476,0.005793983,0.5160392,0.4669273],"study_design_scores_gemma":[0.0001560779,0.0002744848,0.02541963,0.0004445704,0.0003517632,0.001222643,0.0004366365,0.0946523,0.02576969,0.01163473,0.8394484,0.0001891935],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.04371475,0.2381789,0.5153899,0.03193738,0.02653613,0.0009976866,0.004980212,0.01297542,0.1252897],"genre_scores_gemma":[0.1341383,0.1370493,0.2328103,0.001685126,0.006205347,0.0003311847,0.007439535,0.002268699,0.4780722],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1470524,"threshold_uncertainty_score":0.2923928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01138267786719538,"score_gpt":0.2738418441167159,"score_spread":0.2624591662495205,"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."}}