{"id":"W3173654308","doi":"10.1038/s41597-021-00948-1","title":"Profiling the small non-coding RNA transcriptome of the human placenta","year":2021,"lang":"en","type":"article","venue":"Scientific Data","topic":"Cancer-related molecular mechanisms research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Children's Hospital; University of British Columbia; Canadian Centre for Applied Research in Cancer Control; Izaak Walton Killam Health Centre","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; Canadian Institutes of Health Research; National Institutes of Health","keywords":"Transcriptome; Biology; microRNA; Placenta; Gene expression profiling; RNA; Computational biology; Genetics; Gene expression; Gene; Small nucleolar RNA; Bioinformatics; Fetus; Pregnancy; Non-coding RNA","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001753905,0.0001379332,0.0002293295,0.0005773564,0.0002055722,0.0004254378,0.00009573628,0.0001600485,0.0006061704],"category_scores_gemma":[0.0005361954,0.0001208617,0.0002242615,0.0005644342,0.0001430546,0.0001076677,0.0002108877,0.0002095148,0.0003862508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009332161,"about_ca_system_score_gemma":0.000231882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008142584,"about_ca_topic_score_gemma":0.001206345,"domain_scores_codex":[0.9998497,0.00002452401,0.00001055284,0.00005310525,0.00004331457,0.00001880085],"domain_scores_gemma":[0.9998705,0.00004151727,0.00002756328,0.00001701277,0.00003098488,0.00001233302],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001946722,0.00001032927,0.01649103,0.0001179587,0.00003703374,0.0001530695,0.0002184219,0.0002345878,0.9722819,0.0001045512,0.000167256,0.009989095],"study_design_scores_gemma":[0.00002735269,0.0006205398,0.5402793,0.00008471234,0.0002718324,0.00310777,0.0007638605,0.007350586,0.4170481,0.0009251343,0.02947458,0.00004610657],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.9773932,0.003492756,0.01194746,0.00009869338,0.00002536498,0.00005886455,0.005091759,0.0001146302,0.001777328],"genre_scores_gemma":[0.9668903,0.002786054,0.01901648,0.0001951351,0.00003995594,0.0001096088,0.009020013,0.00009860007,0.001843751],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.0008142584,"threshold_uncertainty_score":0.002027869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0531514596618521,"score_gpt":0.3115871794189427,"score_spread":0.2584357197570906,"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."}}