{"id":"W1498733767","doi":"10.1016/s0079-6123(06)65010-3","title":"Coordinate transformations and sensory integration in the detection of spatial orientation and self-motion: from models to experiments","year":2007,"lang":"en","type":"review","venue":"Progress in brain research","topic":"Vestibular and auditory disorders","field":"Neuroscience","cited_by":37,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Orientation (vector space); Computer vision; Motion (physics); Translation (biology); Inertial frame of reference; Computer science; Artificial intelligence; Accelerometer; Reference frame; Position (finance); Vestibular system; Representation (politics); Inertial measurement unit; Rotation (mathematics); Mathematics; Physics; Classical mechanics; Frame (networking); Geometry; Neuroscience; Psychology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001582322,0.0001543621,0.0003080802,0.0006565467,0.0001245942,0.00009449464,0.0001928019,0.0001491788,0.000003305691],"category_scores_gemma":[0.0002488058,0.0001182718,0.00003424317,0.0008249659,0.0002028158,0.0002685424,0.00005053986,0.000502152,0.000002647215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008422745,"about_ca_system_score_gemma":0.00005340443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001162734,"about_ca_topic_score_gemma":0.000215046,"domain_scores_codex":[0.997096,0.001277888,0.0004245178,0.0003958006,0.0005596551,0.0002461361],"domain_scores_gemma":[0.9988195,0.000804923,0.00008679753,0.0001785773,0.00006093894,0.00004927174],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001825529,0.0001031375,0.00002830832,0.000530017,0.000002688437,0.00000515283,0.00481425,0.00001656247,0.0001007993,0.0001486252,0.000004037764,0.9942282],"study_design_scores_gemma":[0.01306059,0.005316861,0.005829092,0.05375457,0.0004391325,0.000299939,0.02734766,0.1698716,0.05101154,0.01893786,0.6490743,0.005056822],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01804995,0.9530373,0.02227377,0.0003666786,0.0002939026,0.005421209,0.00009114393,0.00004349268,0.0004226031],"genre_scores_gemma":[0.3916576,0.6072465,0.0002743037,0.00003346806,0.00007520267,0.000642255,0.00003105421,0.0000244199,0.00001523523],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9891713,"threshold_uncertainty_score":0.4822982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2070635214619265,"score_gpt":0.4611844484387751,"score_spread":0.2541209269768486,"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."}}