{"id":"W2563161448","doi":"10.1109/icip.2016.7532508","title":"Quality assessment of monocular 3D inference","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Safran Electronics (Canada)","funders":"","keywords":"Inference; Computer science; Ground truth; Artificial intelligence; Similarity (geometry); Monocular; Data mining; Quality (philosophy); Pattern recognition (psychology); Machine learning; Computer vision; Image (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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01017309,0.001365721,0.00169956,0.004382695,0.0008625079,0.003533404,0.002292357,0.001649583,0.002784371],"category_scores_gemma":[0.03651052,0.0006604298,0.001361323,0.002544312,0.001541161,0.002861899,0.00405642,0.001163138,0.0008113311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001663532,"about_ca_system_score_gemma":0.00136434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007410355,"about_ca_topic_score_gemma":0.006490227,"domain_scores_codex":[0.9896306,0.002488129,0.0007162142,0.001721393,0.005135521,0.0003081571],"domain_scores_gemma":[0.9791037,0.007904993,0.001909841,0.004851312,0.005850462,0.0003795853],"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":[0.00131555,0.0001502997,0.02635625,0.001226234,0.0006356647,0.0002714779,0.0005869847,0.2962062,0.02129247,0.02105742,0.0106756,0.6202259],"study_design_scores_gemma":[0.00003741974,0.0001685531,0.01083616,0.0001473516,0.00007808514,0.0004493706,0.000183129,0.9455768,0.01946604,0.01708978,0.005874997,0.00009240318],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03125911,0.001874551,0.9613906,0.0002555104,0.00009063957,0.00008206889,0.001439001,0.001603079,0.00200541],"genre_scores_gemma":[0.4766409,0.001075513,0.5131055,0.0002184559,0.0001181772,0.0001141751,0.006809181,0.0007559925,0.001162075],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01017309,"threshold_uncertainty_score":0.05380112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05839675343516443,"score_gpt":0.4133738933389131,"score_spread":0.3549771399037486,"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."}}