{"id":"W4311283135","doi":"10.1038/s41586-022-05622-z","title":"Programming multicellular assembly with synthetic cell adhesion molecules","year":2022,"lang":"en","type":"article","venue":"Nature","topic":"Cellular Mechanics and Interactions","field":"Biochemistry, Genetics and Molecular Biology","cited_by":165,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"National Institute of Neurological Disorders and Stroke; National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; University of California, San Francisco; Damon Runyon Cancer Research Foundation; National Cancer Institute; National Institutes of Health; National Science Foundation","keywords":"Multicellular organism; Cell adhesion molecule; Nectin; Cell adhesion; Adhesion; Intracellular; Cell biology; Cell; Extracellular; Biology; Chemistry; Biochemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001833262,0.0003770747,0.0001876542,0.0002811596,0.0001544018,0.000464963,0.0003418516,0.0002077759,0.0009434978],"category_scores_gemma":[0.0002873621,0.0002224401,0.0001844032,0.000177718,0.0003525796,0.0002741218,0.0005608834,0.00037749,0.00028158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000298314,"about_ca_system_score_gemma":0.0001386204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001521753,"about_ca_topic_score_gemma":0.0003407516,"domain_scores_codex":[0.9998273,0.00002665299,0.00001425511,0.00003349577,0.00006182891,0.00003645201],"domain_scores_gemma":[0.9997711,0.00005196734,0.00007934994,0.00003335693,0.00002601014,0.00003825931],"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":[0.00002340878,0.00002593547,0.0002617349,0.00004398341,0.000008582423,0.00008209333,0.00002921904,0.003128675,0.9878768,0.004585465,0.0001269292,0.003807217],"study_design_scores_gemma":[0.00002315053,0.0001763523,0.0008648995,0.000008996701,0.00001597156,0.0001539238,0.00003248604,0.03154995,0.9550112,0.001504524,0.01063747,0.00002100063],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9172917,0.0005499819,0.07403894,0.0001276949,0.0001035806,0.0000767214,0.0001247304,0.0004162224,0.007270484],"genre_scores_gemma":[0.9671532,0.0003576,0.03051625,0.00005381857,0.00001529995,0.00007318271,0.00008961489,0.0000822773,0.00165878],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009434978,"threshold_uncertainty_score":0.003156364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004079972006778016,"score_gpt":0.2215714813434295,"score_spread":0.2174915093366515,"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."}}