{"id":"W2070074822","doi":"10.1016/j.media.2011.08.002","title":"A constrained independent component analysis technique for artery–vein separation of two-photon laser scanning microscopy images of the cerebral microvasculature","year":2011,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Independent component analysis; Cerebral blood flow; Biomedical engineering; Artificial intelligence; Hemodynamics; Computer science; Pattern recognition (psychology); Medicine; Cardiology","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":[0.0006966674,0.0008355181,0.0005750818,0.001001982,0.0005411898,0.0006384985,0.0008437752,0.0008053857,0.001944104],"category_scores_gemma":[0.001963452,0.0005015592,0.001040013,0.001193773,0.0004694868,0.000617183,0.0007844294,0.001462836,0.0009227563],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003812574,"about_ca_system_score_gemma":0.001474351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004166407,"about_ca_topic_score_gemma":0.005692265,"domain_scores_codex":[0.9996579,0.0001074792,0.00001997541,0.00006069409,0.0001303311,0.00002354529],"domain_scores_gemma":[0.9993225,0.0003042251,0.00005236102,0.00008585858,0.0002078794,0.00002714165],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002672017,0.0001415799,0.0004680413,0.0002569597,0.000213315,0.0001252888,0.0001286275,0.03995676,0.2128561,0.01774653,0.005494046,0.7223456],"study_design_scores_gemma":[0.00004071213,0.000106659,0.002550238,0.00002991439,0.0001339761,0.000379559,0.00002801527,0.890716,0.08438709,0.01052524,0.01099724,0.000105372],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001548976,0.00009587471,0.9979031,0.00003571282,0.00001744028,0.00001840375,0.00003151146,0.0002032253,0.000145712],"genre_scores_gemma":[0.02410611,0.0003268426,0.9738646,0.00004179441,0.00003984948,0.0001366195,0.0001467691,0.0001229077,0.001214433],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004166407,"threshold_uncertainty_score":0.008284271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01244601493709853,"score_gpt":0.2970938518775387,"score_spread":0.2846478369404402,"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."}}