{"id":"W4394378926","doi":"10.6084/m9.figshare.20222621","title":"Additional file 6 of APEX1 regulates alternative splicing of key tumorigenesis genes in non-small-cell lung cancer","year":2022,"lang":"en","type":"dataset","venue":"Figshare","topic":"Cancer-related gene regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Carcinogenesis; Gene; Biology; Alternative splicing; Lung cancer; Cancer research; Genetics; Key (lock); RNA splicing; Computational biology; Oncology; Medicine; RNA; Exon","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":[0.000867628,0.001577805,0.001696215,0.001906971,0.0007633701,0.002041089,0.001995493,0.001797646,0.4548602],"category_scores_gemma":[0.0083482,0.0005711406,0.001586917,0.003253907,0.0002942847,0.001227349,0.001161436,0.001212332,0.09399836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001052112,"about_ca_system_score_gemma":0.001683681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008644035,"about_ca_topic_score_gemma":0.01746456,"domain_scores_codex":[0.9993954,0.00008012236,0.00007860136,0.0002221815,0.000117901,0.0001057293],"domain_scores_gemma":[0.9955649,0.002931468,0.0003137026,0.0003961478,0.0005516916,0.000242004],"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":[0.0004007031,0.00006427638,0.004274812,0.004253175,0.0001486105,0.00009079978,0.00004686523,0.0007007479,0.0004098262,0.0006086273,0.9846661,0.004335458],"study_design_scores_gemma":[0.004503941,0.0001953514,0.03509703,0.002455541,0.0004663444,0.0005391198,0.0002018809,0.001640549,0.00174949,0.006342029,0.9466826,0.0001261783],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007549219,0.00002498354,0.0000309249,0.00002626758,0.000005589327,0.000006088586,0.9995858,0.00007379695,0.0001709493],"genre_scores_gemma":[0.001665766,0.00007739371,0.0003684027,0.0001176279,0.00001314647,0.0001546041,0.9965158,0.0001189455,0.0009684413],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4548602,"threshold_uncertainty_score":0.7775759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0101304864826348,"score_gpt":0.2426493170255111,"score_spread":0.2325188305428763,"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."}}