{"id":"W4398820593","doi":"10.7910/dvn/ubrdcl/iuxk9k","title":"TDF_vector_map.cpg","year":2019,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Computational Physics and Python Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"CpG site; Vector (molecular biology); Vector map; Computer science; Biology; Artificial intelligence; Genetics; DNA methylation; Gene","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":["insufficient_payload"],"category_scores_codex":[0.0001375544,0.0002526663,0.0002527627,0.000145515,0.0001027412,0.0003021375,0.002411783,0.000125532,0.003833508],"category_scores_gemma":[0.00002698512,0.0002611518,0.0001235216,0.0003529176,0.00003235695,0.0003860121,0.001136646,0.0003060771,0.3605937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005496399,"about_ca_system_score_gemma":0.0002311359,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001594921,"about_ca_topic_score_gemma":0.00001798587,"domain_scores_codex":[0.998387,0.00004315312,0.0002467793,0.0006465716,0.0004281033,0.0002484267],"domain_scores_gemma":[0.9967608,0.0001500155,0.0001921879,0.002677538,0.0001041961,0.0001152546],"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":[0.000001468499,0.00005997907,5.180081e-7,0.00003073629,0.00002623743,0.000007919149,0.00000519257,0.0001048988,0.000005790213,0.01808331,0.9811932,0.0004807176],"study_design_scores_gemma":[0.0001464108,0.0000196026,0.00004067353,0.00001937557,0.00001979731,0.000007602368,0.000001084612,0.0025234,0.00000472447,0.002870541,0.9940457,0.0003010608],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[7.043835e-7,7.302659e-7,0.07056805,0.00002969517,0.0008007002,0.000235212,0.9278397,0.00007464787,0.0004505525],"genre_scores_gemma":[0.00001515163,0.00003319796,0.003994663,0.000753295,0.000262066,0.0000530943,0.9945206,0.00001151907,0.0003564243],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3567602,"threshold_uncertainty_score":0.9999841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02191968325410353,"score_gpt":0.2608769244291961,"score_spread":0.2389572411750926,"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."}}