{"id":"W8865236","doi":"10.1007/978-3-540-76386-4_36","title":"Information Fusion for Multi-camera and Multi-body Structure and Motion","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Computer vision; Artificial intelligence; Structure from motion; Motion (physics); Computer science; Motion estimation; Motion field; Fusion; Motion analysis; Sensor fusion","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004474389,0.0003638917,0.0003062074,0.0007265907,0.0003314219,0.0005124532,0.0007015331,0.0002280454,0.000003337265],"category_scores_gemma":[0.0001113604,0.0003187525,0.00004513516,0.0002519811,0.0003629268,0.001907658,0.0007374293,0.0004405934,0.000002773111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001006578,"about_ca_system_score_gemma":0.00008363419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008001864,"about_ca_topic_score_gemma":0.00001867307,"domain_scores_codex":[0.9980725,0.0000120118,0.0004016295,0.000688398,0.0004194303,0.0004060071],"domain_scores_gemma":[0.9986828,0.000182345,0.0002569105,0.0004777057,0.000250105,0.0001501106],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004835762,0.000007073881,0.00005228678,0.00004213603,0.000002174784,0.000002306287,0.0007561696,0.001124209,0.0003108836,0.002944042,0.000002415358,0.9947515],"study_design_scores_gemma":[0.0007126724,0.00008404348,0.000816989,0.0001750037,0.000004050571,0.00005164001,6.587474e-7,0.9835813,0.0009858056,0.01159906,0.001608914,0.0003798589],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001851712,0.0003344537,0.9977519,0.0002309455,0.0007948407,0.0005447608,0.00001090585,0.00009358209,0.00005342056],"genre_scores_gemma":[0.0316926,0.00007541628,0.9664899,0.00154778,0.0001128532,0.000003303139,0.00001239313,0.00001458998,0.00005113797],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9943716,"threshold_uncertainty_score":0.9999264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02463562162864454,"score_gpt":0.2954153025716119,"score_spread":0.2707796809429674,"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."}}