{"id":"W4398984026","doi":"10.7910/dvn/tfks8z/lkhat6","title":"MT_Fig2.m","year":2019,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Chromatin Remodeling and Cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science","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":[0.0001175008,0.000252485,0.0002192908,0.0000435258,0.00004696351,0.00004133395,0.0005123177,0.0003976496,0.007840499],"category_scores_gemma":[0.00007710228,0.0002493422,0.0001337611,0.00004198767,0.00004052036,0.000002767612,0.0003818114,0.0001981724,0.06821679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002301272,"about_ca_system_score_gemma":0.0001767895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008758992,"about_ca_topic_score_gemma":0.00004404807,"domain_scores_codex":[0.998812,0.00003650257,0.0002032733,0.0005127505,0.0001878898,0.0002475513],"domain_scores_gemma":[0.9981731,0.000006813726,0.0001216101,0.001571995,0.00005014319,0.00007639339],"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":[0.00003231652,0.00002575974,0.000001805068,0.0001040253,0.00006541546,0.000006888377,0.000001479594,0.00005610563,0.002658624,6.372301e-7,0.996801,0.0002460015],"study_design_scores_gemma":[0.0003419233,0.00007053567,0.00000305417,0.00005461547,0.00006290623,0.0000166272,0.000009594255,0.0000329416,0.0008647863,0.000002432371,0.9982237,0.0003169121],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002150387,0.00001285424,0.00006797838,0.000002168327,0.0007714148,0.000150697,0.9983838,0.00001008962,0.0003859416],"genre_scores_gemma":[0.00004808019,0.0009613858,0.0001500794,0.0005344336,0.0006822317,0.00001330897,0.9956503,0.00002676309,0.001933447],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06037628,"threshold_uncertainty_score":0.9999959,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01471106897545854,"score_gpt":0.2579956325168865,"score_spread":0.243284563541428,"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."}}