{"id":"W4244081486","doi":"10.21203/rs.3.rs-25157/v3","title":"Depressive Effectiveness of Vigabatrin (y-Vinyl-GABA), an Antiepileptic Drug, in Intermediate-conductance Calcium-Activated Potassium Channels in Human Glioma Cells","year":2020,"lang":"en","type":"preprint","venue":"Research Square","topic":"Neuroscience and Neuropharmacology Research","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"National Cheng Kung University Hospital; National Cheng Kung University; Ministry of Science and Technology, Taiwan","keywords":"Vigabatrin; Antiepileptic drug; Potassium; Conductance; Glioma; Drug; Pharmacology; Calcium; Calcium-activated potassium channel; Potassium channel; Chemistry; Medicine; Neuroscience; Epilepsy; Psychology; Anticonvulsant; Cancer research; Internal medicine; Physics","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":[0.00007482881,0.0001722679,0.000214739,0.0001144373,0.00007887894,0.0002224416,0.0001764631,0.000247943,0.0007917043],"category_scores_gemma":[0.00008542508,0.00007021355,0.0001996021,0.0001306865,0.0001177492,0.0001400174,0.0001084985,0.0003140659,0.0002213638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002050695,"about_ca_system_score_gemma":0.0001311418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001365058,"about_ca_topic_score_gemma":0.001008637,"domain_scores_codex":[0.9999067,0.00001609134,0.00001227384,0.00001823676,0.00002136812,0.00002538231],"domain_scores_gemma":[0.9999672,0.000007101828,0.000006072042,0.000004512372,0.000004971644,0.0000100721],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002643637,0.00003746257,0.0003053662,0.0000414703,0.000007103559,0.00004687424,0.00001821033,0.00004688399,0.9980709,0.00005583462,0.00005645659,0.001049038],"study_design_scores_gemma":[0.00007676824,0.001276873,0.01828875,0.00001063378,0.00003566356,0.000267478,0.00008242253,0.001311639,0.9768403,0.00004951735,0.001753489,0.000006636382],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965016,0.001693278,0.0003751586,0.00004968113,0.00002343713,0.000009765402,0.0003111495,0.00002505614,0.001010989],"genre_scores_gemma":[0.9982152,0.0006559916,0.0002596576,0.00002902141,0.000003430067,0.0000128895,0.0002742675,0.000002611621,0.0005469198],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001365058,"threshold_uncertainty_score":0.002714217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1208263422040452,"score_gpt":0.4365052494327398,"score_spread":0.3156789072286946,"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."}}