{"id":"W2000362325","doi":"10.1016/j.cellbi.2008.03.005","title":"JNK as a positive regulator of angiogenic potential in endothelial cells","year":2008,"lang":"en","type":"article","venue":"Cell Biology International","topic":"Angiogenesis and VEGF in Cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; York University","keywords":"Angiogenesis; Cell biology; c-jun; Kinase; Regulator; Endothelial stem cell; Matrix metalloproteinase; Protein kinase A; Vascular endothelial growth factor A; Chemistry; Extracellular matrix; Cell growth; Gene silencing; Vascular endothelial growth factor; Biology; Transcription factor; Cancer research; In vitro; Biochemistry; VEGF receptors; Gene","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005878229,0.0001010703,0.0001165323,0.00007111794,0.00002551884,0.000002160846,0.0002063451,0.0001611583,0.0002086375],"category_scores_gemma":[0.00001143372,0.00009695871,0.0001500775,0.00004282784,0.000156079,0.000002561398,0.000081242,0.00004276985,0.00002783947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001907217,"about_ca_system_score_gemma":0.00008430659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007701294,"about_ca_topic_score_gemma":0.00001095195,"domain_scores_codex":[0.9992945,0.0000388113,0.0002007093,0.0002502339,0.0000705055,0.0001452242],"domain_scores_gemma":[0.9996508,0.000009061328,0.00009106311,0.000131033,0.00008526654,0.00003281896],"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":[0.0001736577,0.00008110022,0.01044973,0.000001839261,0.00005588551,0.00001199712,0.00003437905,0.00007231483,0.9879715,0.0001517867,0.0006826378,0.0003131005],"study_design_scores_gemma":[0.0007101531,0.0002061646,0.008574787,0.000004562069,0.000007225623,0.00002953549,0.00001754791,0.00004793277,0.9811261,0.0000761206,0.009088883,0.0001109975],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926782,0.0005271775,0.0003225432,0.00006791678,0.0005336034,0.00007872413,0.0001603757,0.000003621018,0.0056279],"genre_scores_gemma":[0.9970502,0.0004127287,0.0002828726,0.0001963387,0.0003463624,0.00001102805,0.0001942482,0.00001065661,0.001495563],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008406245,"threshold_uncertainty_score":0.3953862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005990163647557857,"score_gpt":0.2366436875287485,"score_spread":0.2306535238811906,"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."}}