{"id":"W4390403330","doi":"10.26685/urncst.530","title":"Investigating SHP and PCSK9 Interactions in Cholesterol-Mediated Cardiovascular Diseases: A Research Protocol","year":2023,"lang":"en","type":"article","venue":"Undergraduate Research in Natural and Clinical Science and Technology (URNCST) Journal","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Queen's University; University of Calgary","funders":"","keywords":"PCSK9; Transcription factor; Proprotein convertase; Downregulation and upregulation; Small heterodimer partner; Kexin; Biology; Small interfering RNA; Cell biology; Liver X receptor; Knockout mouse; Farnesoid X receptor; Gene silencing; Electrophoretic mobility shift assay; Nuclear receptor; LDL receptor; Cholesterol; Receptor; Lipoprotein; Endocrinology; Biochemistry; Gene; Transfection","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":[0.002086384,0.001461741,0.001292943,0.001115296,0.001602549,0.0007518812,0.001614958,0.001469999,0.04995162],"category_scores_gemma":[0.0009861614,0.0007298751,0.00144649,0.0009585502,0.000525991,0.0006826925,0.001191008,0.001563421,0.01603927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006901947,"about_ca_system_score_gemma":0.00279984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006074263,"about_ca_topic_score_gemma":0.001166112,"domain_scores_codex":[0.9986065,0.0002670631,0.0001738855,0.000294508,0.0004371509,0.0002209217],"domain_scores_gemma":[0.9991697,0.0001472163,0.00008903933,0.0001567927,0.0003082335,0.0001289822],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00352177,0.001046692,0.0005835342,0.004945559,0.00008118519,0.0005730513,0.0002219348,0.0004936807,0.9008694,0.006164776,0.03292,0.04857828],"study_design_scores_gemma":[0.001196698,0.00590161,0.002914606,0.0005333658,0.000279422,0.001108993,0.0001581267,0.000668856,0.3633115,0.001605406,0.6222251,0.00009627618],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"protocol","genre_scores_codex":[0.1754808,0.04661382,0.3250448,0.007571741,0.008625925,0.2375253,0.08883095,0.006071174,0.1042354],"genre_scores_gemma":[0.08221267,0.05188378,0.1935133,0.003373036,0.001265883,0.3541823,0.09578965,0.0005104932,0.2172689],"genre_candidate":"protocol","genre_consensus":null,"teacher_disagreement_score":0.04995162,"threshold_uncertainty_score":0.1671048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1556145861489014,"score_gpt":0.5059649445165254,"score_spread":0.3503503583676241,"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."}}