{"id":"W4403666775","doi":"10.1016/s2589-7500(24)00154-7","title":"Unleashing the strengths of unlabelled data in deep learning-assisted pan-cancer abdominal organ quantification: the FLARE22 challenge","year":2024,"lang":"en","type":"review","venue":"The Lancet Digital Health","topic":"AI in cancer detection","field":"Computer Science","cited_by":103,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; Toronto Rehabilitation Institute; University Health Network","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cancer; Medicine; Artificial intelligence; Deep learning; Medical physics; Computer science; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":["open_science"],"consensus_categories":[],"category_scores_codex":[0.002842547,0.0004328882,0.001348928,0.0001257097,0.0004015694,0.0006224411,0.006357757,0.0001512492,0.000009252724],"category_scores_gemma":[0.000281631,0.0002038441,0.0001789321,0.001758192,0.0002192402,0.000565625,0.001559032,0.001768323,0.00008431811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000388864,"about_ca_system_score_gemma":0.001138669,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002727488,"about_ca_topic_score_gemma":0.001108655,"domain_scores_codex":[0.9958664,0.0008819386,0.00107425,0.0009059943,0.0006650063,0.0006063883],"domain_scores_gemma":[0.9936048,0.001673055,0.00104506,0.003530357,0.00007904016,0.0000676905],"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":[0.000009118437,0.00003329973,0.000004978229,0.004127567,0.00008369867,0.00000271099,0.0009051425,0.00001391963,4.158316e-8,0.002436073,0.001055729,0.9913277],"study_design_scores_gemma":[0.0002090917,0.0001084665,0.00007582729,0.00694395,0.0001238911,0.000049411,0.0002724126,0.007257099,4.055269e-7,0.0007426217,0.9839357,0.0002811361],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00001129411,0.9799315,0.003011269,0.01398937,0.00101803,0.001143495,0.00016415,0.0001579607,0.0005729524],"genre_scores_gemma":[0.007953298,0.9904193,0.0001187114,0.0001681409,0.0007825252,0.0001635869,0.0001049862,0.00005658471,0.0002328237],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9910466,"threshold_uncertainty_score":0.9990183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1712496576222837,"score_gpt":0.4181453178305883,"score_spread":0.2468956602083046,"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."}}