{"id":"W6950090389","doi":"10.5281/zenodo.7551841","title":"Code repository for Conservation and divergence of canonical and non-canonical imprinting in murids.","year":2023,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Imprinting (psychology); Divergence (linguistics); Code (set theory); Genetic code; Genome; ENCODE","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":[0.0008048743,0.001498709,0.001622495,0.005146338,0.001208909,0.002191514,0.00321979,0.001464936,0.4018166],"category_scores_gemma":[0.004765648,0.000984663,0.0009399044,0.007000593,0.0006135929,0.001985552,0.002068466,0.001658276,0.3297993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001574149,"about_ca_system_score_gemma":0.002450991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01279126,"about_ca_topic_score_gemma":0.01646785,"domain_scores_codex":[0.9991562,0.00005663053,0.0001050952,0.0001443691,0.0004371313,0.0001006377],"domain_scores_gemma":[0.9970933,0.0007035852,0.0003461406,0.000376893,0.001101517,0.0003786111],"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":[0.0001024421,0.00002066375,0.0006917964,0.00124584,0.00002385718,0.00007483902,0.00006786206,0.0003918422,0.001725983,0.004334594,0.9742288,0.01709145],"study_design_scores_gemma":[0.0000797107,0.00002115227,0.002678186,0.0002781517,0.00002654616,0.0001665645,0.0000269035,0.0006218141,0.001606428,0.004783358,0.9896611,0.00005005652],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.0004268134,0.0003253752,0.005269267,0.0001533881,0.000286891,0.0000596168,0.9560917,0.01200775,0.02537913],"genre_scores_gemma":[0.002141383,0.0004028538,0.006582852,0.000150866,0.00005509739,0.0001495245,0.9679961,0.007789874,0.01473142],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.4018166,"threshold_uncertainty_score":0.853236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03204216436163197,"score_gpt":0.2609024930058148,"score_spread":0.2288603286441828,"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."}}