{"id":"W4394189979","doi":"10.6084/m9.figshare.19498041","title":"Additional file 3 of LANDMark: an ensemble approach to the supervised selection of biomarkers in high-throughput sequencing data","year":2022,"lang":"en","type":"dataset","venue":"Figshare","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; University of Guelph","funders":"","keywords":"Landmark; Computer science; Selection (genetic algorithm); Throughput; Computational biology; Machine learning; Artificial intelligence; Data mining; Biology; Operating system","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002887379,0.002300631,0.001757613,0.002491261,0.001009902,0.002401539,0.002908372,0.001870933,0.4605435],"category_scores_gemma":[0.01645321,0.0007282825,0.002036424,0.003517824,0.0005807982,0.0012928,0.001371418,0.001956602,0.1058524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00120054,"about_ca_system_score_gemma":0.002143572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007199457,"about_ca_topic_score_gemma":0.01756375,"domain_scores_codex":[0.9988447,0.0002430812,0.0001300988,0.0004146216,0.000224764,0.0001425617],"domain_scores_gemma":[0.9903368,0.007264568,0.0003478805,0.0008401692,0.0009133703,0.0002971629],"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":[0.0003727009,0.0001112266,0.002796494,0.002174214,0.0001541416,0.00006860163,0.00004482584,0.001457883,0.0003313774,0.0005710996,0.9857011,0.006216343],"study_design_scores_gemma":[0.006211149,0.0003971895,0.02198183,0.001356175,0.0005310468,0.0005418752,0.000241519,0.009651157,0.003156258,0.01516456,0.9405351,0.0002322314],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001507755,0.00002198488,0.0002723479,0.00003880271,0.0000143153,0.00002962708,0.9987946,0.0005070744,0.000170591],"genre_scores_gemma":[0.002185163,0.00004664305,0.002388723,0.0001136248,0.00002268966,0.0005691252,0.9931397,0.00047115,0.001063333],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4605435,"threshold_uncertainty_score":0.7694691,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04393954518143658,"score_gpt":0.2589424991736944,"score_spread":0.2150029539922578,"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."}}