{"id":"W2997253686","doi":"","title":"Sensitivity Assessment for Projector Camera Geometry Reconstruction Systems","year":2019,"lang":"en","type":"article","venue":"Journal of Computational Vision and Imaging Systems","topic":"Optical measurement and interference techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sensitivity (control systems); Projector; Principal (computer security); Point (geometry); Computer vision; Mathematics; Artificial intelligence; Computer science; Geometry; Optics; Physics; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006230848,0.001114805,0.0006946612,0.002333318,0.000505266,0.001565169,0.0007255055,0.001466204,0.002812823],"category_scores_gemma":[0.03695196,0.0005712566,0.0007273323,0.001120734,0.000728361,0.001674175,0.002635906,0.0008397279,0.0006802836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0012826,"about_ca_system_score_gemma":0.0004685782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001676437,"about_ca_topic_score_gemma":0.0009681848,"domain_scores_codex":[0.9924048,0.003176785,0.0002910795,0.0006060067,0.003221766,0.0002996654],"domain_scores_gemma":[0.9779393,0.01624282,0.0008749406,0.001594933,0.003108876,0.0002391695],"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":[0.001627436,0.0001758875,0.01065815,0.0009061735,0.0004784484,0.0004173396,0.0004770428,0.6531684,0.06241761,0.01871041,0.002363625,0.2485995],"study_design_scores_gemma":[0.00001952167,0.0003943622,0.007468066,0.00009852771,0.0001039436,0.0007789929,0.0001435271,0.9412401,0.03865861,0.008700962,0.002302553,0.00009086584],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09698646,0.001815792,0.893287,0.0002891496,0.00005606795,0.0001855092,0.0002282372,0.0007811247,0.006370732],"genre_scores_gemma":[0.8629194,0.001168477,0.1326769,0.0001604476,0.0000595418,0.00009568877,0.0005139076,0.0002065807,0.002198973],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006230848,"threshold_uncertainty_score":0.03295225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0178984451525875,"score_gpt":0.3073568121318725,"score_spread":0.289458366979285,"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."}}