{"id":"W4396867483","doi":"10.2139/ssrn.4820364","title":"Are the Next-Generation Pathogenicity Predictors Applicable to Cancer?","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Pathogenicity; Cancer; Pathogenicity island; Biology; Computer science; Computational biology; Genetics; Microbiology; Genome","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":[],"consensus_categories":[],"category_scores_codex":[0.006753976,0.001501398,0.002399924,0.001868145,0.0006830127,0.004054941,0.001666429,0.001875931,0.006190613],"category_scores_gemma":[0.02866983,0.000713506,0.001316198,0.001772306,0.001305404,0.005085947,0.001642904,0.004500379,0.005633096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005034551,"about_ca_system_score_gemma":0.001566479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001850052,"about_ca_topic_score_gemma":0.002039675,"domain_scores_codex":[0.9980218,0.0006843337,0.0001072968,0.0004784568,0.0004539508,0.0002540934],"domain_scores_gemma":[0.9836766,0.01067808,0.001013765,0.002357632,0.001638093,0.0006359056],"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":[0.001358065,0.0003892206,0.1499135,0.00139754,0.001142119,0.001104103,0.0002587929,0.01421444,0.01263523,0.0246721,0.06137464,0.7315402],"study_design_scores_gemma":[0.0003658362,0.0008674075,0.08204025,0.001149578,0.001706937,0.004567812,0.000556202,0.1461608,0.01343986,0.649318,0.09950517,0.0003221181],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2846196,0.1438739,0.354832,0.1428382,0.01262783,0.0002941502,0.02515746,0.009517891,0.02623902],"genre_scores_gemma":[0.8201416,0.04398591,0.09286954,0.01379968,0.009510696,0.0003083961,0.01235863,0.001112715,0.005912753],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006753976,"threshold_uncertainty_score":0.03571892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01982522508267125,"score_gpt":0.262089287907261,"score_spread":0.2422640628245898,"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."}}