{"id":"W2180000252","doi":"10.1016/j.cll.2011.03.006","title":"Melanoma Margin Assessment","year":2011,"lang":"en","type":"review","venue":"Clinics in Laboratory Medicine","topic":"Cutaneous Melanoma Detection and Management","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"Calgary Laboratory Services; University of Calgary","funders":"","keywords":"Melanoma; Margin (machine learning); Medicine; Cancer research; Computer science; Machine learning","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001816694,0.0006551287,0.003470575,0.000925283,0.00005402559,0.00001106365,0.0003232483,0.0006587882,0.00257504],"category_scores_gemma":[0.0004673461,0.0004875633,0.0003241529,0.001195239,0.0002603957,0.00004312765,0.0001511064,0.001592319,0.0004018473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005568812,"about_ca_system_score_gemma":0.001002173,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001635436,"about_ca_topic_score_gemma":0.00002380249,"domain_scores_codex":[0.9959788,0.0003663989,0.001911919,0.0008277455,0.0004524085,0.0004626939],"domain_scores_gemma":[0.9971458,0.0003887278,0.0006818358,0.001224305,0.0001928991,0.0003664318],"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":[0.00004323084,0.0003385329,0.0001389361,0.01613484,0.0003389608,0.001725291,0.00008256095,5.539077e-8,4.094493e-7,0.002498729,0.01482679,0.9638717],"study_design_scores_gemma":[0.001372373,0.0008680777,0.00009492461,0.01930666,0.001660876,0.0001896937,0.0001030958,0.000005770059,1.767879e-7,0.00007554338,0.9759468,0.0003760231],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00001731934,0.9552661,0.00003351197,0.0001631121,0.003214224,0.001753768,0.00003133366,0.0001504923,0.03937019],"genre_scores_gemma":[0.00002080372,0.992292,0.0005235042,0.0009277467,0.001224397,0.0002301496,0.0001731216,0.0001327194,0.004475499],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9634957,"threshold_uncertainty_score":0.9997576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08583406876859029,"score_gpt":0.4145867446796807,"score_spread":0.3287526759110904,"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."}}