{"id":"W1720791641","doi":"10.48550/arxiv.1503.01832","title":"Linear Global Translation Estimation with Feature Tracks","year":2015,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Outlier; Robustness (evolution); Translation (biology); Computer science; Artificial intelligence; Computer vision; Constraint (computer-aided design); Feature (linguistics); Position (finance); Norm (philosophy); Algorithm; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001257944,0.0002355737,0.0002050472,0.00009319012,0.00009576012,0.00009657908,0.0007794919,0.000180324,0.000005420585],"category_scores_gemma":[0.00001376803,0.0002326762,0.00007899234,0.0005432088,0.000057258,0.0007903884,0.0002811326,0.0004045244,0.00004088694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002085253,"about_ca_system_score_gemma":0.0002158561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002044062,"about_ca_topic_score_gemma":0.00001825223,"domain_scores_codex":[0.9987648,0.0000618299,0.000103542,0.0007320255,0.0001228855,0.0002149906],"domain_scores_gemma":[0.9987936,0.00002315078,0.000158985,0.0006638955,0.0002034587,0.0001569233],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000599831,0.00005634978,0.0005695656,0.00003941188,0.00003197824,0.0001511088,0.0002369383,0.9199395,0.000008072154,0.0173079,0.0004864131,0.0611128],"study_design_scores_gemma":[0.0005291442,0.00004511359,0.0003350517,0.00008409707,0.00002941522,0.0000109728,0.00002717982,0.9684817,0.00002766151,0.02926881,0.0008828617,0.0002779658],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007845897,0.00008295751,0.9876657,0.0003858394,0.0002414661,0.0002068471,0.00001252813,0.000295581,0.003263229],"genre_scores_gemma":[0.80215,0.00002317633,0.1972543,0.00009002439,0.00004213462,3.542415e-7,0.00003233177,0.000009497594,0.0003981467],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7943041,"threshold_uncertainty_score":0.9488261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07636851930763162,"score_gpt":0.2265310761592032,"score_spread":0.1501625568515715,"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."}}