{"id":"W1543689627","doi":"10.1109/iembs.2006.260711","title":"A Localization Method Using 3-axis Magnetoresistive Sensors for Tracking of Capsule Endoscope","year":2006,"lang":"en","type":"article","venue":"","topic":"Gastrointestinal Bleeding Diagnosis and Treatment","field":"Medicine","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Tracking (education); Sensor array; Computer science; Position (finance); Magnetic field; Orientation (vector space); Magnetoresistance; Magnetic dipole; Computer vision; Physics; Artificial intelligence; Acoustics; 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":[0.0005021048,0.000666805,0.0005609607,0.0006517091,0.0002387296,0.0003727032,0.0007661197,0.0008952108,0.0006487871],"category_scores_gemma":[0.0008171826,0.000406091,0.0006202467,0.0004255969,0.0003459659,0.0009044076,0.0004443181,0.0004330614,0.0004803817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002625115,"about_ca_system_score_gemma":0.0004470397,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008083805,"about_ca_topic_score_gemma":0.0008853353,"domain_scores_codex":[0.9995431,0.0001070508,0.00002604948,0.0001067079,0.0001972762,0.00001973018],"domain_scores_gemma":[0.9995994,0.0001065579,0.00008944204,0.00005198995,0.0001288688,0.00002372554],"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":[0.0002168077,0.00007942026,0.001871845,0.0004479623,0.0001337106,0.0003942469,0.0002498801,0.03047087,0.561078,0.005695764,0.002145038,0.3972165],"study_design_scores_gemma":[0.0001263926,0.0008139732,0.006076091,0.00007609589,0.0001952897,0.003031534,0.00007976538,0.7380281,0.2270898,0.002980512,0.02111251,0.0003899553],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004460104,0.0002989642,0.9944326,0.00006665508,0.00003469128,0.00001827846,0.00001189122,0.0004537086,0.0002231253],"genre_scores_gemma":[0.1421869,0.0006249074,0.8551804,0.0001130594,0.00006561561,0.0001033086,0.00005854424,0.00005155506,0.001615727],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0008952108,"threshold_uncertainty_score":0.002655447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03661258449769391,"score_gpt":0.3323760567979884,"score_spread":0.2957634723002945,"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."}}