{"id":"W4393811856","doi":"10.5281/zenodo.3555339","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":"Figshare","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); Physics; Chemistry; Environmental science; Biochemistry; 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":[0.001916799,0.003482628,0.002992516,0.003388594,0.001663379,0.003193961,0.004573378,0.004617652,0.1154626],"category_scores_gemma":[0.007591964,0.001222134,0.002079273,0.005222001,0.0005410281,0.001636853,0.002248239,0.003078686,0.1467557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002454654,"about_ca_system_score_gemma":0.004217837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01826756,"about_ca_topic_score_gemma":0.03284275,"domain_scores_codex":[0.998593,0.000234588,0.0001794021,0.0004346603,0.0003431113,0.0002151945],"domain_scores_gemma":[0.9972529,0.001113176,0.0002574878,0.0005396174,0.0005344157,0.0003024515],"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":[0.0002530784,0.00004498726,0.0007457909,0.002887698,0.00008981348,0.00004327039,0.00002869804,0.0003207991,0.000821627,0.0005175581,0.9915599,0.002686795],"study_design_scores_gemma":[0.001660994,0.00008372993,0.006401511,0.00105152,0.0001745961,0.0001425811,0.00007232794,0.0007486644,0.002406192,0.002653997,0.9845188,0.00008523078],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000103514,0.0001475686,0.00008678944,0.00009608741,0.00002261744,0.00001514223,0.9985196,0.0005651724,0.0004435621],"genre_scores_gemma":[0.0002769953,0.000112576,0.0003396158,0.00008552628,0.000004160888,0.00009987952,0.9985954,0.0001169572,0.0003688641],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1154626,"threshold_uncertainty_score":0.386261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03609436069883026,"score_gpt":0.3132063837151607,"score_spread":0.2771120230163305,"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."}}