{"id":"W4401507296","doi":"10.1109/trpms.2024.3442690","title":"HYPR4D Kernel Method With an Unsupervised 2.5SD+0.5TD Deep Learning Assisted Kernel Matrix","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Radiation and Plasma Medical Sciences","topic":"Optical Imaging and Spectroscopy Techniques","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Pacific Institute for the Mathematical Sciences; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Kernel (algebra); Artificial intelligence; Computer science; Radial basis function kernel; Psychology; Kernel method; Pattern recognition (psychology); Mathematics; Support vector machine; Pure mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.0009319976,0.0001721912,0.0002388612,0.0002723954,0.0003693404,0.0002008462,0.0001084358,0.000150916,0.0006136715],"category_scores_gemma":[0.00005820759,0.000115912,0.00006379776,0.0006783796,0.000387095,0.0002872541,0.000001139573,0.0006276913,0.00002312542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005609343,"about_ca_system_score_gemma":0.0002264276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001025501,"about_ca_topic_score_gemma":0.0000447182,"domain_scores_codex":[0.9980371,0.0001539341,0.0002394239,0.0004759709,0.0008021654,0.0002914222],"domain_scores_gemma":[0.9988828,0.0004520359,0.00002975538,0.0001130309,0.00003348577,0.0004888795],"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":[0.0002262381,0.0003910805,0.0007629449,0.000142057,0.0001068683,0.0001593325,0.0008204225,0.001035976,0.002773207,0.002349776,0.0001171443,0.991115],"study_design_scores_gemma":[0.0008866483,0.002229331,0.001658191,0.0003050678,0.0001713939,0.0005262606,0.0003947559,0.979721,0.009653016,0.0002160849,0.003983676,0.0002546295],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2044307,0.0003020249,0.7843267,0.007082917,0.0003030109,0.0002397485,0.000006041539,0.0007204663,0.002588363],"genre_scores_gemma":[0.9608294,0.0004779348,0.03731573,0.0004036661,0.00008654454,0.00002835012,0.000006259789,0.00001746281,0.0008346597],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9908603,"threshold_uncertainty_score":0.6719272,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02343236627408442,"score_gpt":0.3543237496877761,"score_spread":0.3308913834136917,"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."}}