{"id":"W4393761254","doi":"10.5281/zenodo.8165051","title":"DKC1 eCLIP data","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.001277213,0.003595502,0.001797577,0.004908186,0.001070055,0.002379702,0.003367718,0.00276877,0.1060751],"category_scores_gemma":[0.006589416,0.001305462,0.001880258,0.007856607,0.0007430352,0.001622592,0.002175631,0.002574703,0.137875],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001753848,"about_ca_system_score_gemma":0.003542297,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02585554,"about_ca_topic_score_gemma":0.03757709,"domain_scores_codex":[0.9984846,0.000233985,0.000148469,0.000459827,0.0004174564,0.000255761],"domain_scores_gemma":[0.9969503,0.0008377219,0.0002423752,0.0008923773,0.0007590189,0.0003181894],"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":[0.000119868,0.00004034029,0.0004261387,0.0006528636,0.0000415286,0.00003256507,0.00002842904,0.000597936,0.0005612149,0.000611243,0.9945527,0.00233517],"study_design_scores_gemma":[0.0005276228,0.00005233324,0.002741995,0.0002427501,0.00008440057,0.0001302959,0.00008070734,0.001480412,0.002477982,0.002725613,0.9893897,0.00006622895],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002293361,0.00008132753,0.0001497512,0.00004971589,0.00002365762,0.00001398812,0.9972682,0.001357211,0.00082683],"genre_scores_gemma":[0.00031207,0.00004777121,0.0003256703,0.00004071489,0.000003399734,0.00004150486,0.9985065,0.0002674334,0.0004549288],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1060751,"threshold_uncertainty_score":0.3548566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1299814334959174,"score_gpt":0.3560434903204198,"score_spread":0.2260620568245024,"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."}}