{"id":"W4401978887","doi":"10.1093/database/baae085","title":"Autoinhibited Protein Database: a curated database of autoinhibitory domains and their autoinhibition mechanisms","year":2024,"lang":"en","type":"article","venue":"Database","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Research Foundation of Korea","keywords":"Allosteric regulation; Database; Drug discovery; Mechanism (biology); Computational biology; Computer science; Biology; Bioinformatics; Biochemistry; Enzyme","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":[0.001136443,0.002926768,0.003181201,0.007539623,0.0009081141,0.002965598,0.003190813,0.002367316,0.01627966],"category_scores_gemma":[0.003962887,0.001012975,0.001347108,0.009105717,0.0004866226,0.00244541,0.002806835,0.001734079,0.02382933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001167879,"about_ca_system_score_gemma":0.004386122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004625582,"about_ca_topic_score_gemma":0.00600081,"domain_scores_codex":[0.9991407,0.00007632775,0.0002252292,0.0002081226,0.0002608708,0.00008868227],"domain_scores_gemma":[0.9985008,0.000348755,0.000330028,0.0002334282,0.0002954656,0.0002914908],"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":[0.00232257,0.0003622032,0.009226594,0.03121078,0.0008527897,0.002101926,0.0005459092,0.004734064,0.04470599,0.01050343,0.7757645,0.1176693],"study_design_scores_gemma":[0.0005067466,0.0001741877,0.0164635,0.001598756,0.0004384042,0.00186522,0.0001735807,0.004688744,0.01143721,0.005887317,0.9565895,0.0001769301],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.008008903,0.01109295,0.009647765,0.000298243,0.0001106744,0.0002296175,0.953113,0.01223649,0.005262292],"genre_scores_gemma":[0.006559798,0.003948526,0.01195689,0.0001699751,0.00002429287,0.0002145742,0.9752466,0.0007240339,0.001155369],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01627966,"threshold_uncertainty_score":0.05446094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01885046999893531,"score_gpt":0.2772149938642937,"score_spread":0.2583645238653584,"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."}}