{"id":"W4376871893","doi":"10.1007/s12079-023-00761-y","title":"CCN proteins: opportunities for clinical studies—a personal perspective","year":2023,"lang":"en","type":"review","venue":"Journal of Cell Communication and Signaling","topic":"Connective Tissue Growth Factor Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; University of Toronto","funders":"","keywords":"CYR61; CTGF; Matricellular protein; Perspective (graphical); Biology; Protein family; Computational biology; Signal transduction; Bioinformatics; Neuroscience; Cell biology; Receptor; Extracellular matrix; Gene; Genetics; Growth factor; Computer science","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":[0.001991896,0.0007175916,0.001141185,0.001824724,0.0003160293,0.001599006,0.0007667468,0.002350144,0.004579604],"category_scores_gemma":[0.002738846,0.0001917446,0.0005619049,0.001211346,0.001244236,0.003926707,0.001027834,0.005529348,0.003458662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007800949,"about_ca_system_score_gemma":0.001160023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004244595,"about_ca_topic_score_gemma":0.0009282526,"domain_scores_codex":[0.999551,0.0001077374,0.00005636862,0.00007885861,0.0001620866,0.00004393335],"domain_scores_gemma":[0.9981008,0.0009597308,0.00009260495,0.00006214309,0.000545097,0.0002397079],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001341208,0.00006448019,0.0002909033,0.005740163,0.0000517543,0.0005097244,0.0000970457,0.0001709431,0.00160352,0.01159618,0.1661866,0.8135545],"study_design_scores_gemma":[0.00001708769,0.00007445929,0.000285961,0.001876089,0.0000305934,0.001983961,0.0000563608,0.00004524043,0.0002565569,0.00443478,0.9909222,0.00001662177],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00006434917,0.9897773,0.0002035698,0.006506115,0.002472978,0.000002173608,0.00001036492,0.00000783919,0.0009553711],"genre_scores_gemma":[0.0009135554,0.9876408,0.0004174317,0.004068539,0.005663924,0.00000726524,0.00002720893,0.00000515132,0.001256168],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004579604,"threshold_uncertainty_score":0.0153203,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5597860659883512,"score_gpt":0.5290301155531671,"score_spread":0.03075595043518409,"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."}}