{"id":"W4393617502","doi":"10.5281/zenodo.3252174","title":"RAB1B Expression and Purification","year":2019,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Endoplasmic Reticulum Stress and Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Expression (computer science); Chemistry; Computational biology; Computer science; Biology; Programming language","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":[0.001714571,0.003214659,0.002743096,0.003812063,0.001398184,0.003276936,0.002917913,0.002801869,0.03497227],"category_scores_gemma":[0.005010878,0.0008232952,0.001912414,0.006275719,0.0005371435,0.001025261,0.001692059,0.00239327,0.06666601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001463964,"about_ca_system_score_gemma":0.002244697,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01143358,"about_ca_topic_score_gemma":0.01744257,"domain_scores_codex":[0.9985581,0.0002159524,0.0001544857,0.0006289301,0.0002626628,0.0001798481],"domain_scores_gemma":[0.9987562,0.000391919,0.0001413922,0.0003763359,0.000201893,0.0001321918],"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":[0.0008999855,0.0001219772,0.005600361,0.006906371,0.0004338083,0.0002338509,0.00009762488,0.002729265,0.005987914,0.002072133,0.9613814,0.01353526],"study_design_scores_gemma":[0.0006315949,0.0000735009,0.00839886,0.0007189226,0.0002612537,0.0002554214,0.00007940312,0.001400009,0.003408686,0.00290968,0.9817985,0.00006415982],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000874062,0.0005523862,0.0002968362,0.0000639697,0.00002923756,0.00001863717,0.9966655,0.0007438425,0.0007555209],"genre_scores_gemma":[0.0007632623,0.0001688621,0.0006602704,0.00004426499,0.000002810767,0.00008830336,0.997784,0.000112627,0.0003756242],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03497227,"threshold_uncertainty_score":0.1169939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0196810165150488,"score_gpt":0.247940475265809,"score_spread":0.2282594587507602,"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."}}