{"id":"W4393659911","doi":"10.5281/zenodo.569320","title":"Purification And Grafix Of Full-Length Huntingtin Q23 And Q46 Samples For Cryo Grid Preparation For Electron Microscopy (2017/04/21)","year":2017,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Electron Microscopy Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Huntingtin; Cryo-electron microscopy; Electron microscope; Chemistry; Materials science; Analytical Chemistry (journal); Nanotechnology; Biology; Physics; Biophysics; Chromatography; Optics; 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":[0.00200757,0.003821427,0.002399433,0.004001177,0.001250274,0.003111633,0.003628935,0.003423718,0.05220059],"category_scores_gemma":[0.005324184,0.001136446,0.002014393,0.005368264,0.0006513722,0.00131756,0.002246376,0.002422926,0.07346942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0014179,"about_ca_system_score_gemma":0.00321757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01187101,"about_ca_topic_score_gemma":0.01999147,"domain_scores_codex":[0.9988077,0.0001593918,0.0001388716,0.0004255405,0.0002706225,0.0001979505],"domain_scores_gemma":[0.9984157,0.000484026,0.000193274,0.0004734705,0.0002602793,0.0001731793],"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":[0.0004498363,0.00009388425,0.002383513,0.003553882,0.0002105146,0.000132648,0.00006522133,0.001156522,0.002049646,0.0009137188,0.9834381,0.005552592],"study_design_scores_gemma":[0.001358708,0.00009022805,0.008226487,0.0008782073,0.0002652124,0.000268688,0.0001138592,0.001527792,0.004444691,0.004023162,0.9787106,0.0000922359],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004408313,0.0002347688,0.0002229287,0.00004712381,0.00002704628,0.00001719145,0.9974639,0.001149564,0.0003965974],"genre_scores_gemma":[0.0004703723,0.0001067587,0.00044094,0.00003420136,0.000002779772,0.00005109837,0.9985257,0.0001537891,0.0002145106],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05220059,"threshold_uncertainty_score":0.1746284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02098944238324114,"score_gpt":0.3392278065012443,"score_spread":0.3182383641180032,"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."}}