{"id":"W6977500452","doi":"10.6084/m9.figshare.26986405","title":"Additional file 3 of Conservation and divergence of canonical and non-canonical imprinting in murids","year":2024,"lang":"en","type":"dataset","venue":"Figshare","topic":"Digital and Cyber Forensics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Children's Hospital; University of British Columbia","funders":"","keywords":"Imprinting (psychology); Divergence (linguistics); Table (database); 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001143112,0.001307814,0.001485934,0.002609679,0.001042743,0.001867446,0.002040608,0.001605696,0.6319219],"category_scores_gemma":[0.01350848,0.0005473517,0.00123664,0.004167914,0.0003866914,0.001415681,0.001266633,0.001266165,0.131203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00100721,"about_ca_system_score_gemma":0.001874151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01130416,"about_ca_topic_score_gemma":0.02410062,"domain_scores_codex":[0.9993606,0.00008248959,0.00008946648,0.000240919,0.0001211016,0.000105358],"domain_scores_gemma":[0.9927238,0.005021275,0.0004783146,0.0006236694,0.0008874635,0.0002655103],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001935058,0.00004167809,0.003350809,0.001996594,0.00006617997,0.00006102741,0.00005414061,0.00037318,0.0001951328,0.0005256697,0.9896041,0.003537943],"study_design_scores_gemma":[0.002585059,0.0001321276,0.02965411,0.001958115,0.0002604898,0.0004860262,0.0002995864,0.001117844,0.0009397303,0.006384111,0.9560696,0.0001131484],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006909821,0.00001230387,0.0000368299,0.00001864596,0.000005971361,0.00000751976,0.9996341,0.00006578243,0.0001496188],"genre_scores_gemma":[0.001729416,0.00005548629,0.0005666821,0.0001166417,0.0000169467,0.0002076782,0.9956625,0.0001717065,0.001472867],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6319219,"threshold_uncertainty_score":0.5250187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01422132318690996,"score_gpt":0.2203616454418997,"score_spread":0.2061403222549897,"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."}}