{"id":"W2144540337","doi":"10.1152/ajpheart.01185.2010","title":"Mapping 3-D functional capillary geometry in rat skeletal muscle in vivo","year":2011,"lang":"en","type":"article","venue":"American Journal of Physiology-Heart and Circulatory Physiology","topic":"Cardiovascular Health and Disease Prevention","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Heart, Lung, and Blood Institute; Canadian Institutes of Health Research","keywords":"Hemodynamics; Geometry; Biomedical engineering; Tracking (education); Capillary action; Software; Blood flow; Microcirculation; In vivo; Computer science; Anatomy; Artificial intelligence; Computer vision; Materials science; Mathematics; Engineering; Biology; Medicine","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":[0.0003942782,0.0001707103,0.0008047353,0.0004965679,0.00004725111,0.000002259313,0.00006226389,0.00009751,0.000267776],"category_scores_gemma":[0.00006018903,0.0001549129,0.0003334101,0.00039891,0.0003854135,0.0001160576,0.0000403054,0.0004219414,0.000008709862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007566128,"about_ca_system_score_gemma":0.0002628777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001127978,"about_ca_topic_score_gemma":0.000007316067,"domain_scores_codex":[0.9983683,0.0002760112,0.0005299525,0.0003112,0.0001533674,0.0003611621],"domain_scores_gemma":[0.9991062,0.00006027483,0.0002398616,0.0002200361,0.00009095209,0.0002826526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0003864124,0.0002460334,0.01667955,0.00009028866,0.00008769794,0.00001096134,0.0002696646,0.00002617018,0.9806611,0.00003399143,0.0001249938,0.001383144],"study_design_scores_gemma":[0.001843972,0.0003521205,0.9942832,0.00007742146,0.00004074382,0.0003802985,0.0007784963,0.00003489165,0.0003939975,0.0008027551,0.0008787271,0.0001333756],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974612,0.001891332,0.00000566002,0.00007473123,0.0003200113,0.0001429421,0.00000151259,0.000009548346,0.00009303563],"genre_scores_gemma":[0.9982518,0.0002035347,0.0001528882,0.001053208,0.0003021041,0.000008328807,0.000006546024,0.00001545719,0.000006129957],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9802671,"threshold_uncertainty_score":0.6317165,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01730151890412594,"score_gpt":0.2452352273105479,"score_spread":0.227933708406422,"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."}}