{"id":"W2001221216","doi":"10.1371/journal.pcbi.1000556","title":"A Hidden Markov Model for Single Particle Tracks Quantifies Dynamic Interactions between LFA-1 and the Actin Cytoskeleton","year":2009,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"T-cell and B-cell Immunology","field":"Immunology and Microbiology","cited_by":140,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Alberta Glycomics Centre; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Statistical physics; Markov chain; Cytoskeleton; Biological system; Diffusion; Particle (ecology); Hidden Markov model; Computer science; Physics; Chemistry; Biology; Artificial intelligence; Cell; Machine learning; Quantum mechanics","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":[0.000184587,0.0001855785,0.0003549375,0.00007430368,0.0003760242,0.0000233768,0.0001951324,0.0002001205,0.00006216604],"category_scores_gemma":[0.0001409829,0.0001343939,0.00009812052,0.00009511699,0.0005462373,0.00008220694,0.00005797204,0.0002661989,0.00007210478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003301033,"about_ca_system_score_gemma":0.00004808377,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001710186,"about_ca_topic_score_gemma":0.00002133241,"domain_scores_codex":[0.998677,0.0002498997,0.0003623017,0.0003401404,0.00002327526,0.0003473508],"domain_scores_gemma":[0.9979498,0.001597314,0.0001536136,0.0001554789,0.0001230324,0.00002070852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006395723,0.0002576363,0.0003750146,0.00000881911,0.0002854675,5.549802e-7,0.0005797612,0.0002129304,0.9665433,0.009185608,0.0004005705,0.02151073],"study_design_scores_gemma":[0.02662299,0.003455027,0.01132044,0.0001057847,0.001031243,0.0004813513,0.001306866,0.3538671,0.2923254,0.3004941,0.007262352,0.001727389],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9683014,0.0009866686,0.02076359,0.008773204,0.0002399491,0.0004758998,0.0001223844,0.0001000905,0.0002368043],"genre_scores_gemma":[0.9961403,0.00002384551,0.001790799,0.0004701613,0.00003988489,0.00005466478,0.0005378069,0.00001185909,0.0009306993],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6742179,"threshold_uncertainty_score":0.5480422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03037953733764485,"score_gpt":0.2749538702924483,"score_spread":0.2445743329548035,"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."}}