{"id":"W4393594186","doi":"10.5281/zenodo.3383249","title":"Large-scale purification of Q23 and Q54 HTT from Sf9 and EXPI293F expression systems 2019/07/22","year":2019,"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":"University of Toronto","funders":"","keywords":"Sf9; Scale (ratio); Expression (computer science); Chemistry; Computer science; Physics; Biochemistry","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":[0.001691884,0.002999318,0.002163552,0.003239376,0.001060964,0.002634129,0.003418858,0.003603024,0.04834905],"category_scores_gemma":[0.005064761,0.0008211539,0.001845443,0.004691198,0.0005149188,0.00112496,0.001611323,0.002415989,0.07823804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002158178,"about_ca_system_score_gemma":0.002831354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01886367,"about_ca_topic_score_gemma":0.03053638,"domain_scores_codex":[0.9986754,0.0002220375,0.0001899713,0.0003957285,0.0003345649,0.0001822321],"domain_scores_gemma":[0.9980921,0.0007282862,0.0002024139,0.0004306242,0.0003453084,0.0002012465],"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":[0.0003397009,0.00006363305,0.001380067,0.002633497,0.0001365163,0.00007736964,0.00003273363,0.0008133465,0.00124485,0.0008112132,0.988656,0.003810954],"study_design_scores_gemma":[0.001076597,0.00007629881,0.007579463,0.0007102505,0.0001580714,0.0001694499,0.00007091269,0.001172111,0.002616197,0.002348437,0.9839491,0.00007313343],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002019448,0.0001690301,0.0001195137,0.00007322122,0.00001995244,0.00001227917,0.9984543,0.0005232546,0.0004264188],"genre_scores_gemma":[0.0002742125,0.00007381653,0.0002490413,0.00004077481,0.000002052627,0.00004060937,0.9990446,0.00005421805,0.0002206686],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04834905,"threshold_uncertainty_score":0.1617437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03363258993192117,"score_gpt":0.2865478582682242,"score_spread":0.2529152683363031,"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."}}