{"id":"W6892488894","doi":"10.5281/zenodo.10477083","title":"Segzoo: a turnkey system that summarizes genome annotations: data","year":2024,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre","funders":"","keywords":"ENCODE; Turnkey; Metadata; Download; Scripting language; 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":[0.002074305,0.003181821,0.001672511,0.003648064,0.001233452,0.003425648,0.00253021,0.00104937,0.1482231],"category_scores_gemma":[0.005583922,0.001932276,0.001926261,0.00383974,0.000553171,0.002465256,0.002774011,0.002201304,0.1214136],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001524367,"about_ca_system_score_gemma":0.002467934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00817036,"about_ca_topic_score_gemma":0.01065531,"domain_scores_codex":[0.9989328,0.0001435445,0.0001156067,0.0004402603,0.000203483,0.0001642438],"domain_scores_gemma":[0.9977161,0.0007120419,0.000253278,0.0005803926,0.0005259507,0.000212261],"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":[0.00108884,0.00003381955,0.002081019,0.001252244,0.0001545643,0.0001946998,0.0002651882,0.0003808693,0.01002418,0.001474323,0.9609814,0.02206882],"study_design_scores_gemma":[0.0003248799,0.0001114504,0.005077905,0.0003024234,0.000200097,0.0003226082,0.000273859,0.002300086,0.02448118,0.006097384,0.9603169,0.0001912026],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.001956166,0.0004644454,0.03742516,0.0002907054,0.0003960989,0.0002564593,0.6610772,0.2884862,0.009647576],"genre_scores_gemma":[0.007678682,0.0003985031,0.03855774,0.0005840486,0.00007518047,0.0008097105,0.8551959,0.08732934,0.009370899],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1482231,"threshold_uncertainty_score":0.4958558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0540411191035288,"score_gpt":0.2592821207307366,"score_spread":0.2052410016272078,"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."}}