{"id":"W2980119938","doi":"10.1049/htl.2019.0080","title":"Determining blood flow direction from short neurovascular surgical microscope videos","year":2019,"lang":"en","type":"article","venue":"Healthcare Technology Letters","topic":"Optical Imaging and Spectroscopy Techniques","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Ontario Research Foundation","keywords":"Neurovascular bundle; Blood flow; Imaging phantom; Computer science; Biomedical engineering; Microscope; Surgical planning; Computer vision; Medicine; Radiology; Surgery; Pathology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001668242,0.0002601909,0.0005691283,0.0003728998,0.00009938623,0.00002519285,0.0001782428,0.0003836827,0.00006670853],"category_scores_gemma":[0.00006402053,0.0002461118,0.00015563,0.0004136761,0.0001963464,0.00007809933,0.00009001458,0.001002602,0.00009834555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001084994,"about_ca_system_score_gemma":0.00005573532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001849445,"about_ca_topic_score_gemma":0.000009917763,"domain_scores_codex":[0.9980277,0.00006727699,0.0003782693,0.0006958895,0.0002492565,0.0005816241],"domain_scores_gemma":[0.9988583,0.00007102879,0.00005386437,0.0007941591,0.00006917509,0.000153464],"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":[0.0000755491,0.0001294106,0.4874902,0.0001164431,0.0001001418,0.001068269,0.00005025962,0.000001719676,0.4885314,0.00007910096,0.0005522521,0.0218053],"study_design_scores_gemma":[0.00416021,0.002311767,0.06370363,0.001299946,0.000604752,0.003651578,0.0001700484,0.003000495,0.8864037,0.0004837897,0.03298849,0.001221547],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9407207,0.0005389869,0.0004827544,0.05516642,0.0003449501,0.0005514128,0.000007558364,0.001953598,0.0002336265],"genre_scores_gemma":[0.9662532,0.0001873004,0.02727726,0.005914557,0.0001490351,0.00006162254,0.00003718607,0.00006057608,0.00005921597],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4237866,"threshold_uncertainty_score":0.9999991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008723219134582242,"score_gpt":0.2887142997782381,"score_spread":0.2799910806436559,"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."}}