{"id":"W2805767354","doi":"10.1038/s41598-018-27216-4","title":"Super Resolution Network Analysis Defines the Molecular Architecture of Caveolae and Caveolin-1 Scaffolds","year":2018,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Caveolin-1 and cellular processes","field":"Biochemistry, Genetics and Molecular Biology","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; China Scholarship Council; British Columbia Knowledge Development Fund; Prostate Cancer Canada","keywords":"Caveolae; Modularity (biology); Pipeline (software); Topology (electrical circuits); Coat protein; Cluster analysis; Computer science; Resolution (logic); Caveolin 1; Physics; Artificial intelligence; Chemistry; Biology; Combinatorics; Mathematics; Cell biology; Membrane","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":[0.0004229598,0.0003638306,0.0003901657,0.002125032,0.0003148306,0.0007921174,0.0005011901,0.0004079311,0.00106313],"category_scores_gemma":[0.001434561,0.0002900126,0.0006579395,0.00125551,0.0003368756,0.0009972906,0.0005055486,0.0004075305,0.0002214299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007792843,"about_ca_system_score_gemma":0.0004829107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005668906,"about_ca_topic_score_gemma":0.007367276,"domain_scores_codex":[0.999773,0.00004499196,0.0000115505,0.00007894099,0.0000551201,0.00003643724],"domain_scores_gemma":[0.9993918,0.000279545,0.000128249,0.00006981576,0.00009370792,0.00003683084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003417169,0.0001153033,0.04765476,0.0005302742,0.0002879405,0.0004164177,0.0007065931,0.6322187,0.1775676,0.01868219,0.001651654,0.1198269],"study_design_scores_gemma":[0.000003282106,0.00001189113,0.008152483,0.000006002668,0.00001492184,0.00004697762,0.00004283407,0.9815578,0.004609577,0.005099554,0.0004470565,0.000007523318],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5545775,0.0003340756,0.441494,0.0001709112,0.000006749947,0.0000493059,0.001103549,0.001038916,0.001224938],"genre_scores_gemma":[0.865739,0.0002929887,0.1313874,0.0000274445,0.000008170844,0.00007632792,0.001787084,0.0001090918,0.0005725959],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005668906,"threshold_uncertainty_score":0.01127183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004563310483303888,"score_gpt":0.2172893916612434,"score_spread":0.2127260811779395,"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."}}