{"id":"W2971818215","doi":"10.1016/j.celrep.2019.07.102","title":"Metastatic Tumor Cells Exploit Their Adhesion Repertoire to Counteract Shear Forces during Intravascular Arrest","year":2019,"lang":"en","type":"article","venue":"Cell Reports","topic":"Cellular Mechanics and Interactions","field":"Biochemistry, Genetics and Molecular Biology","cited_by":124,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institut National Du Cancer; Ligue Contre le Cancer; Université de Strasbourg; Centre National de la Recherche Scientifique; CNIB; European Commission; Association pour la Recherche sur le Cancer; Institut National de la Santé et de la Recherche Médicale; Massachusetts Institute of Technology","keywords":"Extravasation; Adhesion; Integrin; Circulating tumor cell; Cell adhesion molecule; Cell adhesion; CD44; Metastasis; Cell biology; Fibronectin; Receptor; Chemistry; Cancer research; Biology; Immunology; Medicine; Cancer; Cell; Extracellular matrix; Internal medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002116653,0.0002292101,0.0002339474,0.00006819511,0.0001068462,0.00006618806,0.0001370422,0.00006412972,0.0003044361],"category_scores_gemma":[0.00004367185,0.0002019714,0.0002130763,0.00008659253,0.00001304525,0.00001398611,0.0001409775,0.0001249309,0.0001287833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003449505,"about_ca_system_score_gemma":0.00006167892,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004297398,"about_ca_topic_score_gemma":0.00001253068,"domain_scores_codex":[0.9984305,0.00003994891,0.0004084089,0.0006181423,0.0001916352,0.0003113627],"domain_scores_gemma":[0.998678,0.00001220073,0.0001913019,0.0008588828,0.0000983161,0.0001612836],"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":[0.00003527901,0.0000800402,0.0001419443,0.00005755132,0.00004157042,0.0001836537,0.00009182566,0.0002603651,0.9978943,0.000003368155,0.001009981,0.0002001481],"study_design_scores_gemma":[0.0001505247,0.0001873443,0.00007920597,0.00004962703,0.00002198813,0.0002083598,0.0002869566,0.0001690703,0.8709922,0.00001947025,0.1276026,0.0002325794],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956232,0.0004485573,0.0004645785,0.00003419684,0.001263944,0.0004494002,0.00000938318,0.00002280826,0.001683935],"genre_scores_gemma":[0.9947301,0.000118161,0.000309337,0.0002182569,0.0001591746,0.00003912883,0.0001110239,0.00005186983,0.004262985],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.126902,"threshold_uncertainty_score":0.8236156,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006749835253534649,"score_gpt":0.2150056993252641,"score_spread":0.2082558640717295,"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."}}