{"id":"W4393557052","doi":"10.5281/zenodo.3383263","title":"Large-scale purification of Q23 and Q54 HTT-HAP40 from Sf9 expression system 2019/07/29","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; Physics; Computer science; Biochemistry; Quantum mechanics; Recombinant DNA","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":[0.001680904,0.003036805,0.002080224,0.003312224,0.001023702,0.002423103,0.00321271,0.003191369,0.04361985],"category_scores_gemma":[0.004852289,0.0008004435,0.001800435,0.004901918,0.0004892601,0.001060409,0.001615704,0.002066228,0.07522036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001993336,"about_ca_system_score_gemma":0.00300501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02082703,"about_ca_topic_score_gemma":0.03264669,"domain_scores_codex":[0.9986286,0.0002337245,0.0001902386,0.0004113758,0.0003453803,0.0001907204],"domain_scores_gemma":[0.9980742,0.0006505886,0.0002232479,0.0004456723,0.0003948131,0.0002115207],"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":[0.0004022839,0.00006801881,0.001553731,0.002867368,0.0001500994,0.00006993684,0.0000318044,0.0007575925,0.001223735,0.0006651946,0.9879895,0.004220779],"study_design_scores_gemma":[0.001089433,0.00008111259,0.008982482,0.0007202771,0.0001829001,0.0001504818,0.00007422739,0.0009677094,0.002577233,0.001862831,0.9832408,0.00007054931],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000237803,0.0001835762,0.0001100271,0.00006433722,0.00001953306,0.00001263922,0.9984912,0.0004432501,0.000437633],"genre_scores_gemma":[0.000286663,0.00007321421,0.0002145605,0.00003242621,0.000002128079,0.000038669,0.9990626,0.00004681975,0.0002428716],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04361985,"threshold_uncertainty_score":0.1459229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03207466935413448,"score_gpt":0.283547821694606,"score_spread":0.2514731523404715,"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."}}