{"id":"W4394291327","doi":"10.6084/m9.figshare.14053257","title":"Additional file 5 of Genome-wide identification and functional prediction of long non-coding RNAs in Sprague-Dawley rats during heat stress","year":2021,"lang":"en","type":"dataset","venue":"Figshare","topic":"Cancer-related molecular mechanisms research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Identification (biology); Computational biology; Heat stress; Long non-coding RNA; Genome; Coding (social sciences); Biology; Non-coding RNA; Genetics; microRNA; RNA; Gene; Mathematics; Statistics","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":[0.001082646,0.001635847,0.001621277,0.002022181,0.0009518662,0.00188287,0.002209225,0.001854793,0.5083993],"category_scores_gemma":[0.008123118,0.0006381359,0.001218381,0.003055303,0.0003358177,0.001242382,0.001273827,0.001377928,0.1145142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001054612,"about_ca_system_score_gemma":0.001695911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009015635,"about_ca_topic_score_gemma":0.0182676,"domain_scores_codex":[0.999397,0.00007913574,0.00008615848,0.0002238471,0.000109235,0.0001046392],"domain_scores_gemma":[0.9957598,0.002691192,0.00033042,0.0003739592,0.0005896927,0.0002548906],"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":[0.0003705398,0.0001076225,0.004519628,0.00381854,0.0001194796,0.00008916573,0.00005521246,0.0006901782,0.0005829149,0.0005653254,0.9845541,0.004527339],"study_design_scores_gemma":[0.003870099,0.0002752487,0.03890357,0.002206899,0.0003625585,0.0005620829,0.0002687137,0.001908133,0.002050059,0.005920582,0.9435132,0.0001587349],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007400443,0.00001380684,0.00004559998,0.00001904421,0.000005129577,0.000009678641,0.9996305,0.00007885427,0.0001233157],"genre_scores_gemma":[0.001095945,0.00003819371,0.0004655863,0.00008688262,0.00000910057,0.0002061669,0.9971665,0.00009404962,0.0008375875],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5083993,"threshold_uncertainty_score":0.7012087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01564921191345308,"score_gpt":0.2373932289278134,"score_spread":0.2217440170143603,"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."}}