{"id":"W6990165077","doi":"","title":"2D to 3D conversion with direct geometrical search and approximation spaces","year":2007,"lang":"en","type":"other","venue":"Library and Archives Canada (Government of Canada)","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Fundamental matrix (linear differential equation); Reprojection error; Context (archaeology); Object (grammar); Point (geometry); Process (computing); Image (mathematics); Point set registration","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000008754901,0.0001704107,0.0002123877,0.000133554,0.00004213817,0.00002287132,0.00006903063,0.00004724291,0.00005129931],"category_scores_gemma":[0.000001396157,0.0001537025,0.000008353106,0.0001687578,0.00003382308,0.00006233846,0.00003575478,0.00009491662,5.524117e-9],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008875359,"about_ca_system_score_gemma":0.0001750453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002158323,"about_ca_topic_score_gemma":0.008372447,"domain_scores_codex":[0.9985583,0.00001697881,0.0001231009,0.0001723567,0.0009339417,0.0001952511],"domain_scores_gemma":[0.999563,0.00008185177,0.00003319165,0.0001077995,4.403542e-7,0.0002136689],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002493141,0.0002096843,0.05691836,0.01543952,0.002000194,0.0009895994,0.0009343878,0.3413502,0.01487859,0.08025362,0.3347654,0.1497673],"study_design_scores_gemma":[0.001162117,0.0003645883,0.009667154,0.001142305,0.0001039146,0.00001155363,0.001362581,0.2622745,0.04332343,0.0000284133,0.679171,0.001388502],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.004225095,0.0005892158,0.009105968,0.000347988,0.000141409,0.000318727,0.0001500835,0.00004922698,0.9850723],"genre_scores_gemma":[0.7393832,0.001305867,0.01619694,0.0007770921,0.0002331523,0.000009166019,0.00009961784,0.0004701214,0.2415248],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7435474,"threshold_uncertainty_score":0.6267807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003094420221944954,"score_gpt":0.1380230548715924,"score_spread":0.1349286346496475,"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."}}