{"id":"W2401276712","doi":"10.3233/978-1-61499-474-9-183","title":"Validation of a Computerized Technique for Automatically Tracking and Measuring the Inferior Vena Cava in Ultrasound Imagery","year":2014,"lang":"en","type":"article","venue":"Studies in health technology and informatics","topic":"Hemodynamic Monitoring and Therapy","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre For Cold Ocean Resources Engineering; Memorial University of Newfoundland","funders":"","keywords":"Inferior vena cava; Computer science; Computer vision; Image quality; Artificial intelligence; Speckle pattern; Tracking (education); Ultrasound; Radiology; Medicine; Image (mathematics)","routes":{"ca_aff":true,"ca_fund":false,"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":[0.005466746,0.0004138093,0.0003703495,0.001030011,0.0002652098,0.001179874,0.001282948,0.001222124,0.001472955],"category_scores_gemma":[0.01697236,0.0002503526,0.0002894819,0.0004719981,0.000646121,0.0005853061,0.0006526585,0.0004867836,0.0006419919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003825812,"about_ca_system_score_gemma":0.0009295559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00177451,"about_ca_topic_score_gemma":0.001675748,"domain_scores_codex":[0.9975287,0.0008691439,0.000203476,0.0004852941,0.0008368688,0.00007642235],"domain_scores_gemma":[0.991836,0.004366867,0.00051792,0.001021063,0.002124977,0.0001331631],"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":[0.0007855344,0.0004089544,0.0178184,0.0004991182,0.0001516912,0.0002338237,0.0005123253,0.01966664,0.5305153,0.001325972,0.001314766,0.4267676],"study_design_scores_gemma":[0.0002168163,0.003815524,0.05905045,0.0001702453,0.000233024,0.002683565,0.0003203793,0.43194,0.4894619,0.0009270353,0.01100543,0.000175591],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.182061,0.0004911279,0.8130353,0.0001871836,0.0001317298,0.0006432885,0.0002414003,0.002124164,0.001084805],"genre_scores_gemma":[0.3774649,0.0002747534,0.6202497,0.0001563984,0.00003483681,0.0003435961,0.0003920263,0.0002354382,0.0008483675],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005466746,"threshold_uncertainty_score":0.02891123,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04028136389608598,"score_gpt":0.3574547298960288,"score_spread":0.3171733659999428,"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."}}