{"id":"W1554296077","doi":"10.1117/1.oe.54.5.054107","title":"Calibration of zoom lens with virtual optical pattern","year":2015,"lang":"en","type":"article","venue":"Optical Engineering","topic":"Optical measurement and interference techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Zoom lens; Zoom; Calibration; Computer science; Optics; Grid; Computer vision; Lens (geology); Artificial intelligence; Optical engineering; Physics; Mathematics; Geometry","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":[0.001060593,0.0006749472,0.0004189422,0.0006684787,0.0003303101,0.0008378185,0.0008329254,0.000582552,0.002213034],"category_scores_gemma":[0.003263723,0.0004819583,0.0002458327,0.0006650859,0.0005925032,0.001008402,0.001112848,0.0005993936,0.0005397091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009292353,"about_ca_system_score_gemma":0.0006764605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001134286,"about_ca_topic_score_gemma":0.001307423,"domain_scores_codex":[0.998709,0.0001782091,0.00004921767,0.00030087,0.0007021428,0.00006055696],"domain_scores_gemma":[0.9984096,0.0003042902,0.0002311111,0.0005968673,0.0003736292,0.00008462052],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004432938,0.000130133,0.005324466,0.0003101872,0.00006809356,0.000322239,0.0005402226,0.05857925,0.761943,0.01336416,0.002136931,0.156838],"study_design_scores_gemma":[0.00006843927,0.0003644107,0.008214518,0.00004949512,0.00002459297,0.001329873,0.0001276167,0.2131712,0.7633811,0.003014601,0.01013014,0.0001241133],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2221766,0.0003549872,0.7676237,0.0001917576,0.0001167287,0.0001554754,0.0001936839,0.002135591,0.00705146],"genre_scores_gemma":[0.6567882,0.0001866444,0.3403323,0.0001061491,0.00001313779,0.00007358231,0.0001579979,0.0002660355,0.002075978],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002213034,"threshold_uncertainty_score":0.007403314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03279410100800143,"score_gpt":0.2228480331488079,"score_spread":0.1900539321408065,"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."}}