{"id":"W2617383746","doi":"10.15353/vsnl.v1i1.58","title":"Dermal Radiomics for Melanoma Screening","year":2015,"lang":"en","type":"article","venue":"Vision Letters","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Melanoma; Radiomics; Medicine; Cancer research; Radiology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0004572113,0.0003585004,0.0002842587,0.0005707785,0.00009726953,0.0003981133,0.0003178395,0.0004619124,0.002596626],"category_scores_gemma":[0.001137308,0.0001661085,0.0003664577,0.0002904027,0.0003423652,0.000370648,0.0003762961,0.0004501722,0.001088051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001910475,"about_ca_system_score_gemma":0.0002308344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005250523,"about_ca_topic_score_gemma":0.000898021,"domain_scores_codex":[0.9997477,0.00008646955,0.00001044027,0.0000540354,0.00008360416,0.0000178199],"domain_scores_gemma":[0.9997335,0.0001084058,0.00004040451,0.00004346312,0.0000575177,0.00001663962],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003868886,0.00008116774,0.002116748,0.0003521381,0.00003346484,0.0003340369,0.00006675543,0.02132702,0.3110791,0.004918057,0.003638508,0.6556662],"study_design_scores_gemma":[0.00007718117,0.001359111,0.01167032,0.0001632785,0.00019477,0.004361822,0.0001316344,0.5680113,0.338051,0.01264135,0.06321562,0.0001226017],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05712949,0.00727834,0.9232411,0.000902252,0.000253964,0.0001738487,0.0002642738,0.001967504,0.008789152],"genre_scores_gemma":[0.6783813,0.005510392,0.3075561,0.0008759206,0.0002979772,0.0001289792,0.0004513322,0.0001630843,0.006634851],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002596626,"threshold_uncertainty_score":0.008686543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02477146947393374,"score_gpt":0.3191634294721881,"score_spread":0.2943919599982544,"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."}}