{"id":"W6968518956","doi":"10.5281/zenodo.16782450","title":"Borzoi Human Model Predictor (Linder et al. 2025) using the Genomic API for Model Evaluation (GAME) Framework","year":2025,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Container (type theory); Scripting language; ENCODE; Replicate; Source code; Code (set theory); Sample (material); Interpretation (philosophy)","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":[0.0007303865,0.0002631874,0.0001991682,0.0001431042,0.000839481,0.0003216456,0.0008861703,0.000325957,0.001430389],"category_scores_gemma":[0.0002940398,0.0002470182,0.0001312562,0.0001327175,0.0001384162,0.000008199314,0.0004964535,0.0003336502,0.00008187625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001009652,"about_ca_system_score_gemma":0.00005832267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002371065,"about_ca_topic_score_gemma":0.000002686644,"domain_scores_codex":[0.9981993,0.0002463752,0.000270464,0.0006192689,0.0003352865,0.0003292654],"domain_scores_gemma":[0.9985948,0.00001157712,0.0001745886,0.0006864489,0.0004470173,0.00008557189],"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":[0.000098551,0.0001197465,0.000001016973,0.00009457598,0.0001988534,3.908122e-7,0.0002240674,0.03246273,0.08054391,0.001867725,0.8807466,0.003641823],"study_design_scores_gemma":[0.0005811641,0.00009910839,0.00000325083,0.00008968028,0.00009909909,0.000002918542,0.00002846815,0.2292869,0.0006110136,0.000721899,0.7682346,0.000241903],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.002662078,0.001069242,0.8308571,0.0007472021,0.0002802506,0.002321482,0.00168777,0.0003238475,0.160051],"genre_scores_gemma":[0.3071935,0.003880883,0.04048297,0.01460797,0.003231387,0.00000746669,0.05891764,0.03475683,0.5369214],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7903741,"threshold_uncertainty_score":0.9999982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07375884704664674,"score_gpt":0.3182780675039408,"score_spread":0.244519220457294,"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."}}