{"id":"W4308120119","doi":"10.3390/cimb44110361","title":"In Silico Identification of Promising New Pyrazole Derivative-Based Small Molecules for Modulating CRMP2, C-RAF, CYP17, VEGFR, C-KIT, and HDAC—Application towards Cancer Therapeutics","year":2022,"lang":"en","type":"review","venue":"Current Issues in Molecular Biology","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université de Montréal; Hôpital Maisonneuve-Rosemont","funders":"","keywords":"In silico; Pyrazole; Identification (biology); Chemistry; Computational biology; Cancer research; Biology; Stereochemistry; Biochemistry; Gene","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":[0.0002829037,0.000712952,0.001285392,0.0005314223,0.0004167787,0.0006727086,0.0006784655,0.0005797758,0.002329929],"category_scores_gemma":[0.0004213961,0.0003737468,0.001045266,0.000492907,0.0001870859,0.0004092168,0.0003399824,0.0004089117,0.0003223959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006899359,"about_ca_system_score_gemma":0.001197237,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004186562,"about_ca_topic_score_gemma":0.005887353,"domain_scores_codex":[0.9999018,0.00001772865,0.000005950536,0.00001617351,0.00003194774,0.00002643035],"domain_scores_gemma":[0.9998803,0.00005704707,0.00002029722,0.000005736735,0.00001981225,0.00001681396],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000516759,0.0003583246,0.006263306,0.00058011,0.000201768,0.0008824624,0.00004564705,0.934579,0.04232223,0.002870904,0.0008205104,0.01055888],"study_design_scores_gemma":[0.00007508547,0.0003628524,0.0008819579,0.00001573283,0.00008246361,0.00007558479,0.00003472836,0.989321,0.007774368,0.0003585145,0.001002689,0.00001500129],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.963186,0.003033028,0.02316334,0.0002779431,0.00004337193,0.0001895149,0.001110019,0.000386453,0.008610359],"genre_scores_gemma":[0.9695574,0.002306243,0.02456488,0.00008489314,0.000009253021,0.0002336703,0.00143967,0.00005049395,0.001753436],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.004186562,"threshold_uncertainty_score":0.008324385,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1183435036276453,"score_gpt":0.4631923286981856,"score_spread":0.3448488250705403,"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."}}