{"id":"W2566834682","doi":"10.1109/crv.2016.58","title":"Synthetic Viewpoint Prediction","year":2016,"lang":"en","type":"article","venue":"","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Artificial intelligence; Clutter; Object (grammar); Computer vision; Class (philosophy); Simultaneous localization and mapping; Monocular; Bridge (graph theory); Augmented reality; Synthetic data; Robot; Mobile robot; Radar","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":[0.000646617,0.001468366,0.0007777816,0.000704167,0.000330547,0.0009616049,0.001570827,0.001274573,0.004930675],"category_scores_gemma":[0.003101255,0.0004374215,0.001090594,0.0006723881,0.0005903916,0.0009873421,0.001142294,0.001304957,0.002307616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007439453,"about_ca_system_score_gemma":0.0006332622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005809634,"about_ca_topic_score_gemma":0.01036805,"domain_scores_codex":[0.9992443,0.0001232294,0.00002245911,0.0003322739,0.0001916138,0.00008605402],"domain_scores_gemma":[0.9987394,0.0003640287,0.00009109804,0.0004539395,0.0002761115,0.00007542],"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":[0.001442575,0.0004287571,0.01568821,0.0005485858,0.0002593267,0.0005557224,0.0001572526,0.5494074,0.02758316,0.006779179,0.05266605,0.3444837],"study_design_scores_gemma":[0.00004135921,0.0001147774,0.003236088,0.00004061426,0.00001930847,0.0002249267,0.00005052222,0.9772364,0.008800496,0.003509693,0.006702836,0.00002298902],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4463464,0.002406891,0.4832145,0.0008431323,0.001096131,0.000460027,0.02511509,0.01392425,0.02659355],"genre_scores_gemma":[0.7871272,0.0003959428,0.1645658,0.0002702651,0.0001004558,0.0001594161,0.04181492,0.0005156142,0.005050278],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005809634,"threshold_uncertainty_score":0.01649475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01182455229156646,"score_gpt":0.1865869398969834,"score_spread":0.174762387605417,"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."}}