{"id":"W4393508514","doi":"10.5281/zenodo.3555338","title":"Large-scale purification of Q23 and Q54 HTT-HAP40 from Sf9 expression system in PBS 2019/09/16","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); Environmental science; Chemistry; Physics; Biochemistry; Gene; Quantum mechanics","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":[0.001919587,0.003239189,0.002243936,0.003238219,0.001059189,0.002528553,0.003316887,0.003766002,0.0461684],"category_scores_gemma":[0.005711759,0.0008655335,0.002072462,0.004432747,0.0005741759,0.001114022,0.001835328,0.002390245,0.0834562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002114085,"about_ca_system_score_gemma":0.002837704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01790579,"about_ca_topic_score_gemma":0.03086467,"domain_scores_codex":[0.9984208,0.000293289,0.0002130232,0.0005020666,0.0003684054,0.0002023689],"domain_scores_gemma":[0.9978484,0.0007834206,0.0002236431,0.0004943593,0.0004347319,0.0002154828],"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":[0.0003602786,0.00007276929,0.001499455,0.003017334,0.0001496249,0.00007482362,0.00003299615,0.0008089217,0.001042083,0.0006284383,0.9876305,0.004682733],"study_design_scores_gemma":[0.001088995,0.00009141708,0.008422436,0.0008313807,0.0001803653,0.000190154,0.00008500645,0.001160245,0.002477217,0.002183886,0.9832169,0.00007200683],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000231697,0.0002506896,0.0001395378,0.0000932483,0.00002734218,0.00001709492,0.9982917,0.0004908678,0.0004578799],"genre_scores_gemma":[0.0003689531,0.0001004015,0.0003059481,0.00004934626,0.000003565639,0.00006181285,0.9987519,0.00005415369,0.000303885],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0461684,"threshold_uncertainty_score":0.1544486,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03085024068894424,"score_gpt":0.2836759889630828,"score_spread":0.2528257482741385,"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."}}