{"id":"W2289996177","doi":"","title":"ACCURACY OF ELECTROMAGNETIC TRACKING IN AN IMAGE-GUIDED SURGERY SUITE","year":2018,"lang":"en","type":"article","venue":"","topic":"Hermeneutics and Narrative Identity","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Orientation (vector space); Fluoroscopy; Position (finance); Tracking (education); Computer science; Interference (communication); Optics; Noise (video); Electromagnetic interference; Acoustics; Physics; Computer vision; Artificial intelligence; Mathematics; Telecommunications; Geometry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001527781,0.0003329377,0.0003034909,0.0006693061,0.0001924923,0.0008002098,0.0004926877,0.0005271851,0.0005666089],"category_scores_gemma":[0.007811748,0.0001745565,0.0002453522,0.0006228247,0.0002465683,0.0003824915,0.0006656005,0.0002336969,0.0004622088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002841135,"about_ca_system_score_gemma":0.0004516885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001809033,"about_ca_topic_score_gemma":0.001598348,"domain_scores_codex":[0.9982694,0.0003876229,0.0001754047,0.0003525986,0.0007175844,0.0000973535],"domain_scores_gemma":[0.9964817,0.001393541,0.0006746857,0.0004431039,0.0009156624,0.00009129711],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003396956,0.0001992054,0.2309368,0.00058129,0.0002286787,0.0003916411,0.001213324,0.03622261,0.3130848,0.0005509168,0.001278771,0.4119149],"study_design_scores_gemma":[0.00009492593,0.002559355,0.5505988,0.0001466669,0.0003654944,0.001867139,0.0004383852,0.1440645,0.2940835,0.0004012739,0.005153963,0.000226092],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8707089,0.0008584093,0.124752,0.00008837054,0.00005563498,0.00004706959,0.0003478987,0.0009370996,0.002204617],"genre_scores_gemma":[0.9642113,0.000217324,0.0346853,0.00004714888,0.00001052645,0.00002360775,0.0002368215,0.00005976034,0.0005081336],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001809033,"threshold_uncertainty_score":0.008079827,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06703908164189683,"score_gpt":0.3087839763962619,"score_spread":0.2417448947543651,"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."}}